Team Description:

The Data Engineering Team works closely with other teams—neuroscientists, physicists, roboticists, chip designers, pathologists, and mechanical engineers—to build Neuralink’s centralized data aggregation and analysis platform. This data platform collects, organizes, and visualizes a diverse set of data ranging from neural signal recordings and brain histology images to microfabrication manufacturing data. Our team owns projects that drive engineering and experimentation at Neuralink.

We operate like an internal startup – rapidly prototyping and building software that solves problems for the company. If you are obsessed with smooth user experience and love to iterate rapidly on software, you may be a good fit for this role!

 See a talk on our data platform, Neuralake, below:

Job Description and Responsibilities:

As a Software Engineer on the Data Engineering Team, you will have the opportunity to impact engineering and experimentation at Neuralink. You will fully own and drive projects, from interfacing with stakeholders and gathering requirements, to delivering exceptional software. Our ideal candidate has accomplished a record of outstanding achievement in software engineering. Additionally, you will be expected to:

• Build end-to-end data systems to facilitate the easy querying of data
• Build and maintain low-latency pipelines and batch data processing jobs
• Create easy-to-use dashboarding platforms for internal data sharing
• Work directly and iteratively with stakeholders to grow MVPs into mature solutions
• Own the design, development, and testing of software development projects
• Deliver results. You may enjoy thoughtful conversations about problems and perfecting designs, but in the end, you know that what matters is delivering a solution that works
• Be a cross-disciplinary team member. You are excited to work with and learn from software, mechanical, electrical, materials, and biological engineers, as well as neuroscientists. You are comfortable communicating across teams.
• Be resourceful, flexible, and adaptable; no task is too big or too small

Jobs at Neuralink are highly dynamic; depending on your skills and our needs, you may work across a wide range of projects, from interpreting neural data to analyzing histology, developing surgical tools, or creating brand-new BCI approaches. Successful candidates will be highly adaptable, able to deploy core technical and creative skills to tackle a wide range of problems, and have a keen sense of urgency.

Required Qualifications: 

• Most important: Demonstrated leadership in delivering a product or feature, either as a team leader or key contributor
• Evidence of exceptional ability in software engineering
• A bachelor’s degree in Computer Science or equivalent demonstrated work experience
• 1-2 years of experience leading teams and owning the success of a product
• Excellent written and verbal communication skills
• Experience understanding requirements and delivering in an interactive manner
• Experience understanding requirements and delivering iteratively

Preferred Qualifications:

• Experience with building data platforms
• Experience with Python and Rust
• Experience with data analytics systems such as Clickhouse, Delta Lake, Apache Spark, Hadoop, or Snowflake

Note: You do not need to have any of these preferred qualifications in order to be considered for this role! Any exceptional software engineer is encouraged to apply.

ABOUT THE TEAM

Anduril Maritime delivers platforms, systems, and integrated effects in the maritime domain. Our autonomous vehicles (sub-surface and surface) are the cornerstone of these capabilities, and we continually strive to push the boundaries of the possible in terms of endurance, autonomy and mission capability. The Maritime team develops and maintains core products and payloads, and adapts and applies those products to serve a wide variety of defense, IC and commercial customers in US and international markets.

ABOUT THE JOB

As a Software Engineer, Data Engineering on the Maritime Digital Production team, you will build the high-throughput data systems that connect design, manufacturing, and operations into a unified digital thread. You’ll design and implement scalable data architectures that move and transform massive datasets efficiently, supporting everything from geometry access to live production analytics.

In this role, you’ll develop high-performance data access layers and scalable databases, integrate information from systems such as PLM, ERP, and MES, and ensure seamless, reliable data flow across the enterprise. You’ll continuously monitor and optimize performance to meet the demands of real-time, high-speed data operations, and maintain strong documentation to keep the system transparent and auditable.

You’ll work closely with software engineers, data scientists, and manufacturing technologists across Anduril in a high-tech, fast-paced culture of innovation. If you’re driven to build data systems that are fast, resilient, and deeply connected to real-world production, you’ll be helping build the future of digital shipbuilding and the next generation of maritime vehicles.

WHAT YOU'LL DO

• Design and Implement Data Access Layers: Develop high-performance data access layers to handle massive datasets, ensuring quick and efficient data retrieval and processing.
• Database Design and Management: Design, implement, and maintain scalable databases suitable for high-speed, high-throughput data operations.
• Data Integration: Integrate data from various business systems including PLM, ERP, and MES, ensuring seamless and efficient data flow.
• Performance Optimization: Monitor and optimize the performance of data access layers and databases to meet the demands of large-scale, real-time data processing.
• Collaborate with Cross-Functional Teams: Work closely with software engineers, data scientists, and other stakeholders to ensure the data architecture supports various applications and analytical needs.
• Maintain Documentation: Write and maintain comprehensive documentation for data access layers, databases, and data integration processes.

REQUIRED QUALIFICATIONS

• Proficiency in database management systems (e.g., SQL, NoSQL databases like MongoDB, Cassandra).
• Experience with data warehousing solutions (e.g., Amazon Redshift, Google BigQuery).
• Strong understanding of data architecture principles and best practices.
• Proficiency in programming languages used for data engineering (e.g., Python, Java, Scala).
• Experience with big data technologies (e.g., Hadoop, Spark).
• Familiarity with cloud platforms and services (e.g., AWS, Azure, GCP).
• Strong problem-solving skills and ability to handle large volumes of data.
• Excellent collaboration and communication abilities.
• Eligible to obtain and maintain an active U.S. Secret security clearance.

PREFERRED QUALIFICATIONS

• Previous experience in a manufacturing or industrial setting.
• Experience with real-time data processing and stream processing technologies (e.g., Kafka, Flink).
• Knowledge of data governance and data quality management practices.
• Familiarity with containerization (Docker) and orchestration (Kubernetes).

As a Sr. Solutions Architect at Databricks within the Field Engineering org, you will partner with our customers to design scalable data architectures using Databricks technology and services. You have technical depth and business knowledge, and can drive complex technology discussions that express the value of the Databricks platform throughout the sales lifecycle. In partnership with our Account Executives, you will engage with our customers' technical leads, including architects, engineers, and operations teams, with the goal of establishing yourself as a trusted advisor to achieve tangible outcomes. You will work with teams across Databricks and our executive leadership to represent your customers' needs, build valuable customer engagements, and report to the Field Engineering Manager.

The impact you will have:

• You will work with Sales and other essential partners to develop account strategies for your assigned accounts to grow their usage of the platform.
• Establish the Databricks Lakehouse architecture as the standard data architecture for customers through excellent technical account planning.
• You will build and present reference architectures and demo applications for prospects to help them understand how Databricks can be used to achieve their goals to land new users and use cases.
• Capture the technical win by consulting on big data architectures, data engineering pipelines, and data science/machine learning projects; prove out the Databricks technology for strategic customer projects; and validate integrations with cloud services and other 3rd party applications.
• Become an expert in and promote Databricks-inspired open-source projects (Spark, Delta Lake, MLflow, and Koalas) across developer communities through meetups, conferences, and webinars.

What we look for:

• 8+ years in a customer-facing pre-sales or consulting role with expertise in at least one of the following technologies:
• Big data engineering (Ex: Spark, Hadoop, Kafka)
• Data Warehousing & ETL (Ex: SQL, OLTP/OLAP/DSS)
• Data Science and Machine Learning (Ex: pandas, scikit-learn, HPO)
• Data Applications (Ex: Logs Analysis, Threat Detection, Real-time Systems Monitoring, Risk Analysis and more)
• Experience translating a customer's business needs to technology solutions, including establishing buy-in with essential customer stakeholders at all levels of the business.
• Experienced at designing, architecting, and presenting data systems for customers and managing the delivery of production solutions of those data architectures.
• Fluent in SQL and database technology.
• Debug and development experience in at least one of the following languages: Python, Scala, Java, or R.
• [Desired] Built solutions with public cloud providers such as AWS, Azure, or GCP
• [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
• Travel to customers in your region up to 30% of the time.

FEQ127R316

As a Specialist Solutions Architect (SSA) - Cloud Infrastructure & Platform, you will guide customers in the administration and security of their Databricks deployments for a variety of our customers. You will be in a customer-facing role, working with and supporting Solution Architects, which requires hands-on production experience with public cloud - AWS, Azure, and GCP.  SSAs help customers with the design and successful implementation of essential workloads while aligning their technical roadmap to expand the use of the Databricks Platform. As a deep go-to-expert reporting to the Specialist Field Engineering Manager, you will continue to strengthen your technical skills through mentorship, learning, and internal training programs, and establish yourself in an area of specialty - whether that be cloud deployments, security, networking, or more.

The impact you will have:

• Provide technical leadership to guide strategic customers to the successful administration of Databricks, ranging from design to deployment
• Architect production-level deployments, including meeting necessary security and networking requirements 
• Become a technical expert in an area such as cloud platforms, automation, security, networking, or identity management
• Assist Solution Architects with more advanced aspects of the technical sale, including custom proof of concept content and custom architectures
• Provide tutorials and training to improve community adoption (including hackathons and conference presentations)
• Contribute to the Databricks Community

What we look for:

• 5+ years of experience in a technical role with expertise in at least one of the following:
• Cloud Platforms & Architecture: Cloud Native Architecture in CSPs such as AWS, Azure, and GCP, Serverless Architecture.
• Security: Platform security, Network security, Data Security, Gen AI & Model Security, Encryption, Vulnerability Management, Compliance. 
• Networking: Architecture design, implementation, and performance
• Identify management: Provisioning, SCIM, OAuth, SAML, Federation
• Platform Administration: High availability and disaster recovery, cluster management, observability, logging, monitoring, audit, and cost management
• Infrastructure Automation and InfraOps with IaC tools like Terraform
• Maintain and extend the Databricks environment to adapt to evolving complex needs.
• Deep Specialty Expertise in at least one of the following areas:
• Security - understanding how to secure data platforms and manage identities
• Complex deployments
• Public Cloud experience - experience designing data platforms on cloud infrastructure and services, such as AWS, Azure, or GCP, using best practices in cloud security and networking.
• Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent experience through work experience.
• Hands-on experience with Python, Java, or Scala, and proficiency in SQL, and Terraform experience are desirable.
• 2 years of professional experience with Big Data technologies (Ex: Spark, Hadoop, Kafka) and architectures
• 2 years of customer-facing experience in a pre-sales or post-sales role
• Can meet expectations for technical training and role-specific outcomes within 6 months of hire
• This role can be remote, with travel up to 30% when needed

About the Role

You are a Data Engineer, who is passionate about writing beautiful code and building great products. You have an intuitive sense of the right tools and frameworks to use to solve a given problem. You are not afraid to traverse the entire spectrum of the development process from writing code and testing to deploying and managing your systems in production. You are smart but know that there is no substitute for hard work. You have good communication skills, a ‘can do’ entrepreneurial attitude, and a team-oriented mindset.

Key Responsibilities

• Design and build data transformations efficiently and reliably for different purposes (e.g. reporting, growth analysis, multi-dimensional analysis)

• Design and implement reliable, scalable, robust and extensible big data systems that support core products and business

• Establish strong engineering design standards and best practices for both technical and non-technical stakeholders

Required Qualifications and Must-Have Skills

• BS/MS degree in Computer Science or related technical field or equivalent practical experience

• Experience in the Big Data technologies (Hadoop, M/R, Hive, Spark, Flink, Metastore, Presto, Kafka etc.)

• Experience with performing data analysis, data ingestion and data integration

• Experience with ETL (Extraction, Transformation & Loading) and architecting data systems

• Experience with schema design, data modeling and SQL queries

• Hands-on experience using modern AI coding assistants (e.g., Claude Code, Windsurf, or equivalent) to design, implement, and optimize data pipelines and large-scale data processing systems

• Passionate and self-motivated about technologies in the Big Data area

Nice to Have Skills

• Experience with Django framework

• Exposure to AWS

Interpersonal Attributes

• You can work independently as well as part of a team

• You take ownership of projects and drive them to conclusion

• You’re a good communicator and are capable of not just doing the work, but teaching others and explaining the “why” behind complicated technical decisions

• You can present your architecture and designs to cross teams

• You aren’t afraid to roll up your sleeves: This role will evolve over time, and we’ll want you to evolve with it!

Base Salary Range: $179,400.00 - $263,120.00. The base salary range represents the anticipated low and high end of the base salary range for this position. Actual salaries may vary and may be above or below the range based on various factors, including but not limited to work location and experience. The base salary is one component of 6sense’s total compensation package for this position. Other compensation may include a bonus program or commission plan, and stock options if approved by 6sense’s board. In addition, 6sense provides a variety of benefits, including generous health insurance coverage, life, and disability insurance, a 401K employer matching program, paid holidays, self-care days, and paid time off (PTO). #Li-remote

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OPEN POSITION ANNOUNCEMENT!

Data Engineer

Open until filled.

Posted 4/29/2026 San Diego County – hybrid work schedule set by SDCP

About the role:  The San Diego Community Power (SDCP) is seeking a seasoned Data Engineer to join our growing team of analytics experts who will be responsible for designing, maintaining, expanding, and optimizing our data infrastructure for data collection, management, transformation, and access. A key priority of this role will be to assist in SDCP’s development of centralizing its data eco-system to allow for creation of pipelines that convert raw data into usable formats for data analysts and other data consumers to utilize. The Data Engineer will handle the core data aspects of software engineering and data science and utilize software engineering principles to develop algorithms that automate the data flow process. They will collaborate with data and system analysts to build machine learning and analytics infrastructure from testing to deployment. 

WHO IS SAN DIEGO COMMUNITY POWER?

San Diego Community Power is a community-driven, not-for-profit public agency providing cleaner energy to the San Diego region. Formed in 2019, Community Power is the second largest Community Choice Aggregator (CCA) in California, serving nearly 1 million customer accounts across its member agencies: the Cities of San Diego, Chula Vista, Encinitas, Imperial Beach, La Mesa and National City, as well as the unincorporated areas of San Diego County.  

OUR HISTORY

San Diego Community Power was formed in 2019 as a public, not-for-profit community choice aggregator (CCA) in the San Diego region. We began electric service in 2021 and serve five member agencies: San Diego, Chula Vista, Encinitas, La Mesa and Imperial Beach, County of San Diego, and National City. SDCP was formed to bring local control and customer choice to San Diego while also providing clean and renewable energy at competitive rates. By the end of 2023, SDCP will provide electricity for nearly half the electric load in San Diego Gas and Electric’s service territory and will be the second largest CCA in California. For more information, please visit SDCommunityPower.org.

COMMITMENT TO DIVERSITY

At SDCP, we value diversity and are committed to creating an inclusive environment for all employees. We represent a diverse customer base and hope to hire employees that reflect our communities. We provide equal employment opportunities to all applicants for employment and prohibit discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. 

ESSENTIAL DUTIES AND PRIMARY RESPONSIBILITES

• Building and maintaining a centralized cloud-based data infrastructure for optimal extraction, transformation, and loading of data from a wide variety of sources. 
• Assemble large, complex data sets that meet functional/non-functional business requirements. 
• Developing data tools and APIs for data analysis. 
• Deploying and monitoring machine learning algorithms and statistical methods in production environments to solve organizational needs. 
• Ensuring data accessibility and security and implementing company data policies regarding data privacy and confidentiality. 
• Improving data systems reliability, speed, and performance. 
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer trends, operational efficiency, and other key business performance metrics. 
• Collaborating with other internal teams, data analysts, and other stakeholders to understand and optimize how data can be leveraged to meet business needs. 
• Assist in drafting data and analytics’ solicitations and in the selection of consultants. 
• Assist with drafting staff reports and presentations for Board and Committee meetings. 
• Performs other related duties and responsibilities as required. 

MINIMUM KNOWLEDGE, SKILLS, AND ABILITES

• Advance working knowledge of SQL, experience working with relational databases, query authoring (SQL) and working familiarity with various databases. 
• Demonstrated experience in developing API and integrations to support analytics in cloud environment. 
• Experience building and optimizing ‘big data’ data pipelines, architectures, and data sets. 

• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement. 
• Strong analytic skills related to working with unstructured datasets. 
• Build processes supporting data transformation, data structures, metadata, dependency, and workload management. 
• A successful history of manipulating, processing, and extracting value from large, disconnected datasets. 
• Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores. 
• Good understanding of data architecture, data design, data warehousing and data modeling concepts. 
• Strong project management and organizational skills. 
• Experience supporting and working with cross-functional teams in a dynamic environment. 

PREFERRED KNOWLEDGE, SKILLS, AND ABILITES

• Experience in the energy sector and/or supporting the implementation of programs funded by California state agencies (e.g., California Public Utilities Commission, California Energy Commission, California Air Resources Board).
• Ability to strongly represent the organization in various professional engagement settings from local to national convenings (conferences, workshops, executive meetings, etc.).

PREFERRED QUALIFICATIONS, EDUCATION AND EXPERIENCE

Minimum of two (2) to three (3) years of professional experience in a Data Engineer role, preferably in the energy industry with a graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. The candidate should also have experience using the following software/tools:

• Experience with big data tools: Hadoop, Spark, PowerBI, Kafka, etc.
• Experience with AWS, Azure and Google Cloud services.
• Experience with relational SQL and NoSQL databases.
• Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
• Experience with open-source technologies: Python, Pytorch, Flask, Tensorflow or Keras
• Experience with stream-processing systems: Storm, Spark-Streaming, etc.
• Experience with object-oriented/object function scripting languages: Java, C++ etc.
• Experience with batch, micro-batching and real-time data ingestion methodologies.
• Experience with GitHub or similar code repositories

WORK ENVIROMENT & CONDITIONS

Prolonged periods sitting at a desk and working on a computer. The position requires occasional carrying, lifting and/or moving objects up to 25 pounds. Occasional local travel required and reliable transportation to be able to attend SDCP events, meetings, and workshops as needed is expected. At SDCP we work in the communities we serve and in the office. SDCP works to ensure a safe and healthy workplace for employees and in our communities. SDCP requires employees to be fully vaccinated for COVID-19. SDCP is an agency required to adopt and promulgate a Conflict-of-Interest Code (“COI”). The COI code requires employees in designated positions, including those identified under the interim disclosure process to file a Statement of Economic Interests (Form 700) on an annual basis. A Successful candidate accepting this position may be required to file Conflict of Interest forms subject to the regulations of the Fair Political Practices Commission.

COMPENSATION: 

Salary Range: The position salary range is: $84,900 - $110,400; with exact compensation to be determined by SDCP, depending upon experience. 

Benefits: Standard benefits package including but not limited to:

Insurance: SDCP offers group health benefits, including medical, vision, and dental insurance, for eligible FT employees. Also provided is a $100,000 Life & AD&D policy, STD and LTD coverage that is 100% paid by SDCP.

Retirement: SDCP offers a 457(b) plan for employee contributions and contributes 10% of eligible compensation to the employee’s Money Purchase Plan.

Paid Time Off: 11 holidays per year + paid winter holiday (between 12/24-12/31), 160 hours of accrued paid time off per year (increases with time in service), and 96 hours per year of accrued paid sick leave.

This job description may not be inclusive of all assigned duties, responsibilities, or aspects of the job described, and may be amended at the discretion of SDCP as needed. 

As a Data Scientist supporting AI engineers, you will partner with one or more engineering teams, developing actionable insights that guide improvements to the Wayve AI Driver. Using experimental and observational analyses of real and simulated driving, you will help teams advance the functionality, safety, and performance of the Wayve AI Driver, helping to advance Wayve as the leader in end-to-end AI for autonomous mobility.

This means you might:

• Formulate and iterate upon the performance metrics that organize our engineering efforts and guide progress toward commercial success
• Design experiments and targeted off-road measurements to ensure that we deliver product requirements to customers while maintaining safety and performance
• Investigate factors in model training and inference leading to bottlenecks in functionality and performance, identifying and validating hypotheses for unlocking improvements

What we are looking for in our candidate

Essential

• 3+ years experience working in a Data Science role.
• Fluent in querying and building large datasets, writing production-level SQL for use in data-transformation pipelines.
• Prior experience designing robust real-world experiments (e.g. A/B) and critically evaluating test-statistics
• Foundations in the fundamentals behind statistics: testing appropriate distributions, testing the assumptions behind frequentist stats
• Proficient in using a statistical scripting language and data science/ML packages (e.g. python such as pandas, sklearn, statsmodels, scipy or R such as dplyr, caret, stats)
• Well-versed in summarising, visualising and communicating findings in an accessible and compelling way
• Track record of influencing team direction through your findings  
• A bias towards deriving actionable insight that can be used to drive prioritisation and strategy for others.
• Comfortable working asynchronously across time zones with cross-functional partners
• You are deeply curious about building something new and relish the idea of helping to define AV2.0 and how we build it.

Desired

• Practical experience with machine learning (e.g. pytorch). Passion to take research ideas to production.
• Track record of promoting statistical rigour and experimental best practices in your prior roles.
• Prior experience using causal inference/econometric techniques and bayesian methodologies for hypothesis testing.
• Prior experience using large datasets with distributed computing (e.g. spark, hadoop or other map-reduce tech)
• Experience working in a fast-moving tech company or startup.

As a Hunter Solutions Architect on the Digital Natives team, you will shape the future of the big data landscape by working with the most sophisticated data engineering and data science teams in the world.

Reporting to the Field Engineering Manager, you will collaborate with customers, product teams, and the broader customer-facing team to develop architectures and solutions using our platform and APIs. You will guide customers through the competitive landscape, best practices, and implementation; and develop technical champions along the way.

The impact you will have:

• You will partner with the sales team and provide technical leadership to help customers understand how Databricks can help solve their business problems.
• Work directly with prospective, greenfield, customers on their 0 to 1 journey with Databricks 
• Consult on Big Data architectures, implement proof of concepts for strategic projects, spanning data engineering, data science and machine learning, and SQL analysis workflows. As well as validating integrations with cloud services, home grown tools, and other 3rd party applications
• Collaborate with your fellow Solutions Architects, using your skills to support each other and our users
• Become an expert in, promote, and recruit contributors for Databricks inspired open-source projects (Spark, Delta Lake, and MLflow) across the developer community.

What we look for:

• 5+ years in a data engineering, data science, technical architecture, or similar pre-sales/consulting role
• Experience building distributed data systems at scale 
• Comfortable programming in, and debugging, Python and SQL
• Experience using agentic coding harnesses and demonstrable experience scaling your work leveraging them 
• Have built solutions with public cloud providers such as AWS, Azure, or GCP
• Expertise in one of the following:
• Data Engineering technologies (Ex: Spark, Hadoop, Kafka)
• Data Science and Machine Learning technologies (Ex: pandas, scikit-learn, pytorch, Tensorflow)
• Available to travel to customers in your region
• [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
• Nice to have: Databricks Certification

NOTE: If your experience isn’t a perfect match for the job description, but you feel like you’re a good fit for the role, apply.  We want to work with smart, passionate, people who are good at their job, and, a lot of times, those people have non-linear career paths.

As a Data Scientist supporting AI engineers, you will partner with one or more engineering teams, developing actionable insights that guide improvements to the Wayve AI Driver. Using experimental and observational analyses of real and simulated driving, you will help teams advance the functionality, safety, and performance of the Wayve AI Driver, helping to advance Wayve as the leader in end-to-end AI for autonomous mobility.

This means you might:

• Formulate and iterate upon the performance metrics that organize our engineering efforts and guide progress toward commercial success
• Design experiments and targeted off-road measurements to ensure that we deliver product requirements to customers while maintaining safety and performance
• Investigate factors in model training and inference leading to bottlenecks in functionality and performance, identifying and validating hypotheses for unlocking improvements

What we are looking for in our candidate

Essential

• 3+ years experience working in a Data Science role.
• Fluent in querying and building large datasets, writing production-level SQL for use in data-transformation pipelines.
• Prior experience designing robust real-world experiments (e.g. A/B) and critically evaluating test-statistics
• Foundations in the fundamentals behind statistics: testing appropriate distributions, testing the assumptions behind frequentist stats
• Proficient in using a statistical scripting language and data science/ML packages (e.g. python such as pandas, sklearn, statsmodels, scipy or R such as dplyr, caret, stats)
• Well-versed in summarising, visualising and communicating findings in an accessible and compelling way
• Track record of influencing team direction through your findings  
• A bias towards deriving actionable insight that can be used to drive prioritisation and strategy for others.
• Comfortable working asynchronously across time zones with cross-functional partners
• You are deeply curious about building something new and relish the idea of helping to define AV2.0 and how we build it.

Desired

• Practical experience with machine learning (e.g. pytorch). Passion to take research ideas to production.
• Track record of promoting statistical rigour and experimental best practices in your prior roles.
• Prior experience using causal inference/econometric techniques and bayesian methodologies for hypothesis testing.
• Prior experience using large datasets with distributed computing (e.g. spark, hadoop or other map-reduce tech)
• Experience working in a fast-moving tech company or startup.

While candidates in the listed location(s) are encouraged for this role, candidates in other locations will be considered. #LI-REMOTE

As a Solutions Architect on the Digital Natives team, you will shape the future of the big data landscape by working with the most sophisticated data engineering and data science teams in the world.

Reporting to the Field Engineering Manager, you will collaborate with customer stakeholders, product teams, and the broader customer-facing team to develop architectures and solutions using our platform and APIs. You will guide one of our largest AI native customers through the competitive landscape, best practices, and implementation; and develop technical champions along the way.

The impact you will have:

• You will partner with the sales team and provide technical leadership to help customers understand how Databricks can help solve their business problems.
• Consult on Big Data architectures, implement proof of concepts for strategic projects, spanning data engineering, data science and machine learning, and SQL analysis workflows. As well as validating integrations with cloud services, home grown tools, and other 3rd party applications
• Collaborate with your fellow Solutions Architects, using your skills to support each other and our users
• Become an expert in, promote, and recruit contributors for Databricks inspired open-source projects (Spark, Delta Lake, and MLflow) across the developer community.

What we look for:

• 7+ years in a data engineering, data science, technical architecture, or similar pre-sales/consulting role
• Experience building distributed data systems
• Comfortable programming in, and debugging, Python and SQL
• Have built solutions with public cloud providers such as AWS, Azure, or GCP
• Expertise in one of the following:
  • Data Engineering technologies (Ex: Spark, Hadoop, Kafka)
  • Data Science and Machine Learning technologies (Ex: pandas, scikit-learn, pytorch, Tensorflow)
• Available to travel to customers in your region
• [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
• Nice to have: Databricks Certification

NOTE: If your experience isn’t a perfect match for the job description, but you feel like you’re a good fit for the role, apply.  We want to work with smart, passionate, people who are good at their job, and, a lot of times, those people have non-linear career paths.

JOB SUMMARY:

The Manager, Management Consulting will work closely with clients to translate their priorities into innovative data and analytics strategies that support their business priorities and achieve desired outcomes. This position will work on projects that address a wide range of clients’ issues including data strategy, data governance, architecture, technology modernization, business transformation, and analytics adoption. The Manager, Management Consulting will be advising clients on how they can leverage emerging technologies such as cloud services, data science, blockchain, and other capabilities to build competitive advantage.

SUMMARY OF ESSENTIAL JOB FUNCTIONS:

• Meet with clients to understand their needs, perform analyses, formulate hypotheses, and develop actionable plans
• Collaborate closely with client sponsors and other leaders on design of enterprise-wide platforms to accelerate rapid evaluation and implementation of analytical use cases
• Work with functional and technical teams to identify high-priority use cases and design enterprise-wide data platforms
• Develop enterprise data strategies and roadmaps with recommendations based on client needs, leading practices, and emerging vendor solutions
• Design effective operating models that describe how clients can organize their resources and processes to execute their strategic roadmap
• Lead design and execution of technical capability assessments, analyzing results, and presenting recommendations in an effective, logical manner to the client
• Develop and present logical, creative business cases that achieve client support for Company recommendations
• Deliver thoughtful recommendations through compelling presentations and lead facilitated workshops to influence business decisions
• Plan and manage scope, activities, resources, and budget for assigned projects
• Develop effective working relationships directly with clients and internal colleagues
• Support account teams in identifying opportunities and proposing solutions to clients.

REQUIRED SKILLS AND EXPERIENCE:

• Minimum of 8 years of work experience in management consulting
• Minimum of Bachelor’s degree, preferably Master’s degree, in Business, IT, Computer Science, Quantitative Methods, Data Science, or related field
• Minimum of 2 years of experience in one or more industries (e.g., healthcare, financial services, technology, manufacturing, etc.)
• Agile delivery leadership (SDLC, testing, release)
  • Serve as integrated Program Manager from planning to execution; manage scope, requirements, dependencies, resources, schedule, risks/issues, and communications for assigned initiatives.  
  • Lead application development teams, coordinating product owners, business/system analysts, engineers, QA, and release management activities across sprints and releases; establish delivery governance (RAIDs, dashboards, acceptance criteria).  
  • Ensure rigor across the software lifecycle—integrating test strategy (functional, non‑functional, UAT), release readiness, and change/release control practices; drive transparency of status, risks, and burn‑down.  
• Practical knowledge of modern data and analytics technologies in the following categories:
  • Business Intelligence (Power BI, Tableau, Qlik)
  • Machine Learning (R, Python, SAS, SPSS)
  • Data Warehouse (SQL, Snowflake, Oracle, etc.)
  • Big Data (Spark, Hadoop, NoSQL Databases, Data Lakes, and related platforms)
  • Cloud Platforms (Azure, AWS, Google Cloud)
• Strong knowledge of relevant technology trends across the IT and digital landscape and how they can be applied to address real world problems and opportunities
• Team oriented and collaborative working style, with clients and colleagues
• Demonstrated ability to plan, organize, and manage other consultants to achieve project objectives and deliver successful projects
• Highly organized, detail-oriented, excellent time management skills and able to effectively prioritize tasks in a fast-paced, high-volume, and evolving work environment
• Excellent oral, written communication, and presentation skills with an ability to present technical issues to executives and non-technical audience
• Strong proficiency in Microsoft Office (Word, PowerPoint, Outlook, Excel, Teams, etc.)

While candidates in the listed location(s) are encouraged for this role, candidates in other US locations will be considered. #LI-REMOTE

As a Solutions Architect on the Digital Natives team, you will work with the leading data engineering, data science & ML teams in the market to push the boundaries of what big data architectures are capable of. 

Reporting to the Field Engineering Manager, you will collaborate with strategic customers, product teams, and the broader customer-facing team to develop architectures and solutions using our platform and APIs. You will guide customers through the competitive landscape, best practices, and implementation; and develop technical champions along the way.

We are looking for high technical aptitude individuals with a deep sense of ownership and a desire to help customers ship solutions at production scale. Ideal candidates are deeply curious, capable of operating with confidence in ambiguous situations, and are extremely adaptable. 

The impact you will have:

• You will partner with the sales team and provide technical leadership to help customers understand how Databricks can help solve their business problems.
• Drive technical discovery and solution design, focusing on winning competitive deals and accelerating time-to-value in strategic accounts.
• Continuously research & learn new technologies and their implementations on Databricks
• Consult on Big Data architectures, implement proof of concepts for strategic projects, spanning data engineering, data science and machine learning, and SQL analysis workflows. As well as validating integrations with cloud services, home grown tools, and other 3rd party applications
• Collaborate with your fellow Solutions Architects, using your skills to support each other and our customers
• Become an expert in, promote, and recruit contributors for Databricks inspired open-source projects (Spark, Delta Lake, and MLflow) across the developer community.
• Work closely with account executives to create and execute account penetration strategies, focusing on winning technical decision-makers and building new customer champions.
• Build trusted advisor relationships with senior and executive stakeholders by articulating the business value of Databricks in clear, outcomes-driven terms.
  
  

What we look for:

• 5+ years in a data engineering, data science, technical architecture, or similar pre-sales/consulting role
• Experience building distributed data systems
• Comfortable programming in, and debugging, Python and SQL
• Have built solutions with public cloud providers such as AWS, Azure, or GCP
• Expertise in one of the following:
• Data Engineering technologies (Ex: Spark, Hadoop, Kafka)
• Data Science and Machine Learning technologies (Ex: pandas, scikit-learn, pytorch, Tensorflow)
• Strong executive presence with the ability to influence C/VP-level stakeholders and align technical solutions to strategic business priorities.
• Available to travel to customers in your region
• [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
• Nice to have: Databricks Certification
  
  

NOTE: If your experience isn’t a perfect match for the job description, but you feel like you’re a good fit for the role, apply. We want to work with smart, passionate, people who are good at their job, and, a lot of times, those people have non-linear career paths.

FEQ127R13

While candidates in the listed location(s) are encouraged to apply for this role, exceptionally well-qualified candidates in other East Coast locations will also be considered.

Mission

Solutions Architects at Databricks lead the growth of the Databricks Data Intelligence Platform. As a team, we have expertise in cloud platforms, data engineering, data analytics, and data science, machine learning, and AI. As a member of our team, you will exercise and grow your expertise in those areas, using open source projects such as Apache Spark™, Delta Lake, and MLflow. This is a customer-facing role, where you will work with customers, your teammates, the product team, our post-sales team,s and partners, to identify use cases for Databricks, develop architectures and solutions using our platform, and guide customers through the implementation, to accomplish meaningful outcomes for their businesses. In this process, you will build relationships with our customers, identify and cultivate champions, and establish yourself as a trusted advisor. You will report to a Field Engineering Manager within the Financial Services team at Databricks.

The impact you will have:

• Partner with the sales team to help customers understand how Databricks can help solve their business problems
• Provide technical leadership for customers to evaluate and adopt Databricks
• Consult on big data architecture, execute proof of concepts for strategic customer projects, and validate integrations with cloud services and other 3rd party applications
• Build and present reference architectures, how-tos, and demonstrate applications for customers
• Become an expert in, and promote open source projects (Apache Spark™, Delta Lake, MLflow, and Unity Catalog) across developer communities through meetups, conferences, and webinars
• Travel to meet with customers in your territory

What we look for:

• 10+ years in a customer-facing pre-sales role, or consulting role - preferably working with big-data technologies to solve data engineering and big-data analytical challenges
• Experience designing and architecting distributed data systems
• Comfortable programming in, and debugging, at least one of: Python, SQL, Scala, Java, or R
• Experience working with global system integrators, consulting organizations, or financial services technology, or financial services data providers is a positive differentiator 
• Experience building solutions with public cloud providers such as AWS, Azure, or GCP
• Experience with Data Engineering technologies (Ex: Spark, Hadoop, Kafka)
• Experience with Data Warehousing technologies (Ex: SQL, OLTP/OLAP/DSS)
• Undergraduate degree or higher in an engineering or mathematics discipline such as Computer Science, Applied Mathematics, Electrical Engineering, etc.)

P-1399

At Databricks, we are passionate about enabling Data & AI teams to solve the world's toughest problems - from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers, we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for data interaction to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

About the Team:

The Backline Engineering Team serves as the critical bridge between Frontline Support and Engineering. We handle complex technical issues and escalations across the Data and AI ecosystem. With a strong focus on customer success, we are committed to delivering exceptional customer satisfaction by providing deep technical expertise, proactive issue resolution, and continuous platform improvements. We emphasize automation and tooling to enhance troubleshooting efficiency, reduce manual efforts, and improve the overall supportability of the platform and the health of our products. By developing smart solutions and streamlining workflows, we drive operational excellence and ensure a delightful experience for both customers and internal teams.

What your impact will be:

• Act as the ultimate technical escalation point, driving the resolution of the most complex, high-stakes customer issues on the Databricks Platform through deep analysis of core components, metrics, and logs.
• Elevate global team competency by architecting standardized troubleshooting methodologies, comprehensive runbooks, and leading deep-dive technical enablement sessions.
• Champion product supportability and observability, by actively partnering with Engineering and Product teams to influence the roadmap and integrate critical feedback.
• Spearhead strategic automation and tooling initiatives, driving programs that significantly reduce manual toil and improve global MTTR (Mean Time to Resolution) metrics.
• Act as the primary technical liaison between Support and Engineering, driving the enablement strategy for upcoming product features, architectures, and releases.
• Lead cross-functional incident response, demonstrating deep ownership and coordinating seamlessly across Engineering, Escalation, and Support teams to resolve critical requests.
• Participate in weekday and weekend on-call rotations to ensure continuous coverage.

What we look for:

We are looking for candidates who demonstrate deep mastery of one of the following and related areas:

• Application Debugging: Deep expertise in troubleshooting, supporting, and maintaining complex Java, Scala, or Python-based applications
• Big Data Ecosystems: Advanced proficiency in managing, tuning, and resolving issues within distributed computing environments, with a strong emphasis on Apache Spark™ , Hadoop or other Distributed Systems
• Database Management: Proficient at debugging, tuning, and resolving issues in SQL-based relational databases, preferably Postgres
• Automation & Tooling: Advanced proficiency in building automation frameworks and system scripts using Python or bash/shell
• Infrastructure & Networking: Deep foundation in Linux system administration, kernel-level troubleshooting, and complex network diagnostics (e.g., TCP/IP Stack, DNS, routing, packet capture analysis)
• Cloud Skills: Extensive hands-on experience debugging, optimizing, and supporting highly scalable workloads across major cloud platforms (AWS, Azure, or GCP)
• Expert-level diagnostic skills, with a proven track record of pinpointing root causes in highly complex systems through advanced black-box and system-level troubleshooting
• 12+ years of highly technical industry experience in technical support, sustaining engineering or similar roles.
• Bachelor's degree in Computer Science or related fields.

P-256

We are looking for experienced pre-sales professionals who have a successful track record helping large enterprises become more data-driven. Working with the Account Executive (AE), the Retail and CPG SA defines and directs the technical strategy for our largest and important accounts, leading to more widespread use of our products and wider and deeper adoption of ML & AI. You will lean upon your solid background in value selling, technical account management and technical leadership to maximize success in these accounts. While you work with a team that includes hands-on resources who will build proofs of concept and demonstrate Databricks' products, you need to be technical and must understand the relevance and application of ML & AI within a range of use cases important to the target accounts in the Retail and CPG space.

The impact you will have:

• You will work with 1-5 clients as the main technical voice for Databricks
• You will lead your customers on a transformational journey, helping them to evaluate and adopt Databricks as part of their strategy
• You will implement the technical strategy in the account, in close understanding of the strategy
• Build a movement of technical champions within the account
• Align technical strategies around Databricks solutions
• You will provide structured mentorship for other team members

What we look for:

• 5+ years of experience working very large (> $1m ARR), from the Retail and CPG related space
• 3+ years working in a pre sales capacity or supporting sales activity
• Technical in big data, data science and cloud
• An ability in data-driven business transformation, and driving change with data
• 3+ years of experience with design and implementation experience in big data technologies such as Hadoop, NoSQL, MPP, OLTP, and OLAP or full lifecycle data science solutions
• Maintain and extend production data systems to evolve with complex customer needs
• Production programming experience in Python, R, Scala or Java
• Nice to have: Databricks Certification

P-345

At Databricks, our customers challenge us with solving some of the world's toughest data problems. Our customers rely on our Solutions Architect team to understand the technologies that power our platform, the broader cloud and technology ecosystems, and how they can all be brought together to solve these problems.

Solutions Architects at Databricks lead the adoption of the Databricks Unified Analytics Platform. As a member of our team, you will sharpen your skills on open-source projects such as Apache Spark™, MLflow, and Delta Lake to advocate the Lakehouse paradigm on public cloud providers. You will gain expertise in cloud platforms, data engineering, data analytics, data science, and machine learning. In this customer-facing role, you will identify use cases for Databricks, develop architectures and solutions using our platform, and guide customers through implementations to deliver strategic business value. You will build relationships with our customers and establish yourself as a trusted advisor.

Databricks' culture thrives on collaboration and teamwork, and you will contribute your knowledge to our teams by participating in our subject matter expert groups. In this role, you will report to the Solutions Architect Leader supporting the specific business segment.

If you are a technologist interested in Data and AI, and enjoy prototyping solutions for customers, this role is for you.

The impact you will have:

• Provide technical leadership for customers to evaluate and adopt Data and AI solutions from Databricks
• Consult on big data architecture, implement proof of concepts for strategic customer projects, data science and machine learning projects, and validate integrations with cloud services and other 3rd party applications
• Build and present reference architectures, technical guides, and demo applications for customers
• Provide escalated support for critical customer operational issues
• Become an expert in, and evangelize Databricks driven open-source projects (Apache Spark™, Delta Lake, MLflow, Koalas) across developer communities through meetups, conferences, and webinars
• Use your strengths to help your fellow SA's, and drive cross-functional relationships across the company
• Travel to customers (up to 30%, of which 80%+ local to your region)

What we look for:

Solution Architects are customer-facing. You'll need to be comfortable communicating ideas to various audiences through presentations, whiteboarding, architecture discussions, and platform demonstrations.

• 5+ years in a customer-facing pre-sales, technical architecture, or consulting role
• Experience designing and architecting distributed data systems
• Comfortable programming in and debugging at least one of Python, Scala, Java, SQL, or R
• Have built solutions with public cloud providers, such as AWS, Azure, or GCP
• Experience in at least one of the following:
  • Data Engineering technologies (e.g., Spark, Hadoop, Kafka)
  • Data Warehousing (e.g., SQL, OLTP/OLAP/DSS)
  • Data Science and Machine Learning technologies (e.g., pandas, scikit-learn, HPO)
• [Preferred] Degree in a quantitative discipline (e.g., Computer Science, Applied Mathematics, Operations Research, etc.)
• Nice to have: Databricks Certification

P-256

We are looking for experienced pre-sales professionals who have a successful track record helping large enterprises become more data-driven. Working with the Account Executive (AE), the Travel & Hospitality within Retail SA defines and directs the technical strategy for our largest and important accounts, leading to more widespread use of our products and wider and deeper adoption of ML & AI. You will lean upon your solid background in value selling, technical account management and technical leadership to maximize success in these accounts. While you work with a team that includes hands-on resources who will build proofs of concept and demonstrate Databricks' products, you need to be technical and must understand the relevance and application of ML & AI within a range of use cases important to the target accounts in the Retail and CPG space.

The impact you will have:

• You will work with up to 9 clients as the main technical voice for Databricks
• You will lead your customers on a transformational journey, helping them to evaluate and adopt Databricks as part of their strategy
• You will implement the technical strategy in the account, in close understanding of the strategy
• Build a movement of technical champions within the account
• Align technical strategies around Databricks solutions
• You will provide structured mentorship for other team members

What we look for:

• 5+ years of experience working very large (> $1m ARR), from the Retail and CPG related space
• 3+ years working in a pre sales capacity or supporting sales activity
• Technical in big data, data science and cloud
• An ability in data-driven business transformation, and driving change with data
• 3+ years of experience with design and implementation experience in big data technologies such as Hadoop, NoSQL, MPP, OLTP, and OLAP or full lifecycle data science solutions
• Maintain and extend production data systems to evolve with complex customer needs
• Production programming experience in Python, R, Scala or Java
• Nice to have: Databricks Certification

P-344

At Databricks, our customers challenge us with solving some of the world's toughest data problems. Our customers rely on our Solutions Architect team to understand the technologies that power our platform, the broader cloud and technology ecosystems, and how they can all be brought together to solve these problems.

Solutions Architects at Databricks lead the adoption of the Databricks Unified Analytics Platform. As a member of our team, you will sharpen your skills on open-source projects such as Apache Spark™, MLflow, and Delta Lake to advocate the Lakehouse paradigm on public cloud providers. You will gain expertise in cloud platforms, data engineering, data analytics, data science, and machine learning. In this customer-facing role, you will identify use cases for Databricks, develop architectures and solutions using our platform, and guide customers through implementations to deliver strategic business value. You will partner with the sales team to build relationships with our customers and establish yourself as a trusted advisor.

Databricks' culture thrives on collaboration and teamwork, and you will contribute your knowledge to our teams by participating in our subject matter expert groups. In this role, you will report to the Solutions Architect Leader supporting the specific business segment.

If you are a technologist interested in Data and AI, and enjoy prototyping solutions for customers, this role is for you.

The impact you will have:

• Provide technical leadership for customers to evaluate and adopt Data and AI solutions from Databricks
• Consult on big data architecture, implement proof of concepts for strategic customer projects, data science and machine learning projects, and validate integrations with cloud services and other 3rd party applications
• Build and present reference architectures, technical guides, and demo applications for customers
• Provide escalated support for critical customer operational issues
• Become an expert in, and evangelize Databricks driven open-source projects (Apache Spark™, Delta Lake, MLflow, Koalas) across developer communities through meetups, conferences, and webinars
• Use your strengths to help your fellow SA's, and drive cross-functional relationships across the company
• Travel to customers (up to 30%, of which 80%+ local to your region)

What we look for:

Solution Architects are customer-facing. You'll need to be comfortable communicating ideas to various audiences through presentations, whiteboarding, architecture discussions, and platform demonstrations.

• 3+ years in a customer-facing pre-sales, technical architecture, or consulting role
• Experience designing and architecting distributed data systems
• Comfortable programming in and debugging at least one of Python, Scala, Java, SQL, or R
• Have built solutions with public cloud providers, such as AWS, Azure, or GCP
• Experience in at least one of the following:
  • Data Engineering technologies (e.g., Spark, Hadoop, Kafka)
  • Data Warehousing (e.g., SQL, OLTP/OLAP/DSS)
  • Data Science and Machine Learning technologies (e.g., pandas, scikit-learn, HPO)
• [Preferred] Degree in a quantitative discipline (e.g., Computer Science, Applied Mathematics, Operations Research, etc.)
• Nice to have: Databricks Certification

P-256

We are looking for experienced pre-sales professionals who have a successful track record helping large enterprises become more data-driven. Working with the Account Executive (AE), the Retail and CPG SA defines and directs the technical strategy for our largest and important accounts, leading to more widespread use of our products and wider and deeper adoption of ML & AI. You will lean upon your solid background in value selling, technical account management and technical leadership to maximize success in these accounts. While you work with a team that includes hands-on resources who will build proofs of concept and demonstrate Databricks' products, you need to be technical and must understand the relevance and application of ML & AI within a range of use cases important to the target accounts in the Retail and CPG space.

The impact you will have:

• You will work with 1-5 clients as the main technical voice for Databricks
• You will lead your customers on a transformational journey, helping them to evaluate and adopt Databricks as part of their strategy
• You will implement the technical strategy in the account, in close understanding of the strategy
• Build a movement of technical champions within the account
• Align technical strategies around Databricks solutions
• You will provide structured mentorship for other team members

What we look for:

• 5+ years of experience working very large (> $1m ARR), from the Retail and CPG related space
• 3+ years working in a pre sales capacity or supporting sales activity
• Technical in big data, data science and cloud
• An ability in data-driven business transformation, and driving change with data
• 3+ years of experience with design and implementation experience in big data technologies such as Hadoop, NoSQL, MPP, OLTP, and OLAP or full lifecycle data science solutions
• Maintain and extend production data systems to evolve with complex customer needs
• Production programming experience in Python, R, Scala or Java
• Nice to have: Databricks Certification

#LI Remote 

P-186

At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions.

Founded in 2013 by the original creators of Apache Spark™, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest growing SaaS companies in the world.

Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is critical to making customers successful on our platform.

We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above.

Modern data analysis employs sophisticated methods such as machine learning that go well beyond the roll-up and drill-down capabilities of traditional SQL query engines. As a software engineer on the Runtime team at Databricks, you will be building the next generation distributed data storage and processing systems that can outperform specialized SQL query engines in relational query performance, yet provide the expressiveness and programming abstractions to support diverse workloads ranging from ETL to data science.

Below are some example projects:

Apache Spark™: Develop the de facto open source standard framework for big data.

Data Plane Storage: Deliver reliable and high performance services and client libraries for storing and accessing humongous amount of data on cloud storage backends, e.g., AWS S3, Azure Blob Store.

Delta Lake: A storage management system that combines the scale and cost-efficiency of data lakes, the performance and reliability of a data warehouse, and the low latency of streaming. Its higher level abstractions and guarantees, including ACID transactions and time travel, drastically simplify the complexity of real-world data engineering architecture.

Delta Pipelines: It's difficult to manage even a single data engineering pipeline. The goal of the Delta Pipelines project is to make it simple and possible to orchestrate and operate tens of thousands of data pipelines. It provides a higher level abstraction for expressing data pipelines and enables customers to deploy, test & upgrade pipelines and eliminate operational burdens for managing and building high quality data pipelines.

Performance Engineering: Build the next generation query optimizer and execution engine that's fast, tuning free, scalable, and robust.

What we look for:

• BS in Computer Science, related technical field or equivalent practical experience.
• Optional: MS or PhD in databases, distributed systems.
• Comfortable working towards a multi-year vision with incremental deliverables.
• Driven by delivering customer value and impact.
• 8+ years of production level experience in either Java, Scala or C++.
• Strong foundation in algorithms and data structures and their real-world use cases.
• Experience with distributed systems, databases, and big data systems (Apache Spark™, Hadoop).

P-186

At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions.

Founded in 2013 by the original creators of Apache Spark™, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest growing SaaS companies in the world.

Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is critical to making customers successful on our platform.

We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above.

Modern data analysis employs sophisticated methods such as machine learning that go well beyond the roll-up and drill-down capabilities of traditional SQL query engines. As a software engineer on the Runtime team at Databricks, you will be building the next generation distributed data storage and processing systems that can outperform specialized SQL query engines in relational query performance, yet provide the expressiveness and programming abstractions to support diverse workloads ranging from ETL to data science.

Below are some example projects:

Apache Spark™: Develop the de facto open source standard framework for big data.

Data Plane Storage: Deliver reliable and high performance services and client libraries for storing and accessing humongous amount of data on cloud storage backends, e.g., AWS S3, Azure Blob Store.

Delta Lake: A storage management system that combines the scale and cost-efficiency of data lakes, the performance and reliability of a data warehouse, and the low latency of streaming. Its higher level abstractions and guarantees, including ACID transactions and time travel, drastically simplify the complexity of real-world data engineering architecture.

Delta Pipelines: It's difficult to manage even a single data engineering pipeline. The goal of the Delta Pipelines project is to make it simple and possible to orchestrate and operate tens of thousands of data pipelines. It provides a higher level abstraction for expressing data pipelines and enables customers to deploy, test & upgrade pipelines and eliminate operational burdens for managing and building high quality data pipelines.

Performance Engineering: Build the next generation query optimizer and execution engine that's fast, tuning free, scalable, and robust.

What we look for:

• BS in Computer Science, related technical field or equivalent practical experience.
• Optional: MS or PhD in databases, distributed systems.
• Comfortable working towards a multi-year vision with incremental deliverables.
• Driven by delivering customer value and impact.
• 8+ years of production level experience in either Java, Scala or C++.
• Strong foundation in algorithms and data structures and their real-world use cases.
• Experience with distributed systems, databases, and big data systems (Apache Spark™, Hadoop).

P-256

We are looking for experienced pre-sales professionals with a proven track record of helping large enterprises become more data-driven. Working with the Account Executive (AE), the Retail and CPG Sr. SA defines and directs the technical strategy for our largest and most important accounts, leading to more widespread use of our products and wider and deeper adoption of ML & AI. You will lean upon your solid background in value selling, technical account management, and technical leadership to maximize success in these accounts. While you work with a team that includes hands-on resources who will build proofs of concept and demonstrate Databricks' products, you need to be technical and must understand the relevance and application of ML & AI within a range of use cases important to the target accounts in the Retail and CPG space.

The impact you will have:

• You will work with 1-5 clients as the main technical voice for Databricks
• You will lead your customers on a transformational journey, helping them to evaluate and adopt Databricks as part of their strategy
• You will implement the technical strategy in the account, in close understanding of the strategy
• Build a movement of technical champions within the account
• Align technical strategies around Databricks solutions
• You will provide structured mentorship for other team members

What we look for:

• 8+ years of experience working in very large (> $1m ARR), from the Retail and CPG-related space
• 5+ years working in a pre-sales capacity or supporting sales activity
• Technical in big data, data science, and cloud
• An ability in data-driven business transformation and driving change with data
• 3+ years of experience with design and implementation experience in big data technologies such as Hadoop, NoSQL, MPP, OLTP, and OLAP or full lifecycle data science solutions
• Maintain and extend production data systems to evolve with complex customer needs
• Production programming experience in Python, R, Scala, or Java
• Nice to have: Databricks Certification

P-256

We are looking for experienced pre-sales professionals with a proven track record of helping large enterprises become more data-driven. Working with the Account Executive (AE), the Retail and CPG Sr. SA defines and directs the technical strategy for our largest and most important accounts, leading to more widespread use of our products and wider and deeper adoption of ML & AI. You will lean upon your solid background in value selling, technical account management, and technical leadership to maximize success in these accounts. While you work with a team that includes hands-on resources who will build proofs of concept and demonstrate Databricks' products, you need to be technical and must understand the relevance and application of ML & AI within a range of use cases important to the target accounts in the Retail and CPG space.

The impact you will have:

• You will work with 1-5 clients as the main technical voice for Databricks
• You will lead your customers on a transformational journey, helping them to evaluate and adopt Databricks as part of their strategy
• You will implement the technical strategy in the account, with a close understanding of the strategy
• Build a movement of technical champions within the account
• Align technical strategies around Databricks solutions
• You will provide structured mentorship for other team members

What we look for:

• 5+ years of experience working in very large (> $1m ARR), from the Retail and CPG-related space
• 3+ years working in a pre-sales capacity or supporting sales activity
• Technical in big data, data science, and cloud
• An ability in data-driven business transformation and driving change with data
• 3+ years of experience with design and implementation experience in big data technologies such as Hadoop, NoSQL, MPP, OLTP, and OLAP, or full lifecycle data science solutions
• Maintain and extend production data systems to evolve with complex customer needs
• Production programming experience in Python, R, Scala, or Java
• Nice to have: Databricks Certification

LI #Remote

P-59

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

Modern data analysis employs sophisticated methods such as machine learning that go well beyond the roll-up and drill-down capabilities of traditional SQL query engines. As a software engineer on the Runtime team at Databricks, you will be building the next generation distributed data storage and processing systems that can outperform specialized SQL query engines in relational query performance, yet provide the expressiveness and programming abstractions to support diverse workloads ranging from ETL to data science.

Below are some example projects:

Apache Spark™: Develop the de facto open source standard framework for big data.

Data Plane Storage: Provide reliable and high performance services and client libraries for storing and accessing humongous amount of data on cloud storage backends, e.g., AWS S3, Azure Blob Store.

Delta Lake: A storage management system that combines the scale and cost-efficiency of data lakes, the performance and reliability of a data warehouse, and the low latency of streaming. Its higher level abstractions and guarantees, including ACID transactions and time travel, drastically simplify the complexity of real-world data engineering architecture.

Delta Pipelines: It's difficult to manage even a single data engineering pipeline. The goal of the Delta Pipelines project is to make it simple and possible to orchestrate and operate tens of thousands of data pipelines. It provides a higher level abstraction for expressing data pipelines and enables customers to deploy, test & upgrade pipelines and eliminate operational burdens for managing and building high quality data pipelines.

Performance Engineering: Build the next generation query optimizer and execution engine that's fast, tuning free, scalable, and robust.

What we look for:

• BS (or higher) in Computer Science, related technical field or equivalent practical experience.
• Comfortable working towards a multi-year vision with incremental deliverables.
• Motivated by delivering customer value and impact.
• 5+ years of production level experience in either Java, Scala or C++.
• Strong foundation in algorithms and data structures and their real-world use cases.
• Experience with distributed systems, databases, and big data systems (Apache Spark™, Hadoop).

P-59

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

Modern data analysis employs sophisticated methods such as machine learning that go well beyond the roll-up and drill-down capabilities of traditional SQL query engines. As a software engineer on the Runtime team at Databricks, you will be building the next generation distributed data storage and processing systems that can outperform specialized SQL query engines in relational query performance, yet provide the expressiveness and programming abstractions to support diverse workloads ranging from ETL to data science.

Below are some example projects:

Apache Spark™: Develop the de facto open source standard framework for big data.

Data Plane Storage: Provide reliable and high performance services and client libraries for storing and accessing humongous amount of data on cloud storage backends, e.g., AWS S3, Azure Blob Store.

Delta Lake: A storage management system that combines the scale and cost-efficiency of data lakes, the performance and reliability of a data warehouse, and the low latency of streaming. Its higher level abstractions and guarantees, including ACID transactions and time travel, drastically simplify the complexity of real-world data engineering architecture.

Delta Pipelines: It's difficult to manage even a single data engineering pipeline. The goal of the Delta Pipelines project is to make it simple and possible to orchestrate and operate tens of thousands of data pipelines. It provides a higher level abstraction for expressing data pipelines and enables customers to deploy, test & upgrade pipelines and eliminate operational burdens for managing and building high quality data pipelines.

Performance Engineering: Build the next generation query optimizer and execution engine that's fast, tuning free, scalable, and robust.

What we look for:

• BS (or higher) in Computer Science, related technical field or equivalent practical experience.
• Comfortable working towards a multi-year vision with incremental deliverables.
• Motivated by delivering customer value and impact.
• 5+ years of production level experience in either Java, Scala or C++.
• Strong foundation in algorithms and data structures and their real-world use cases.
• Experience with distributed systems, databases, and big data systems (Apache Spark, Hadoop).

About the Role

A unique opportunity to be part of a growing Enterprise Architect team in a well-funded SaaS startup with great customer traction. As the technical anchor to our customer field team, you will work closely with our Customers, providing consultative services and support. Your primary responsibility is to ensure our customers are able to realize the full value of the StarTree solution and in an expedient manner. To do this successfully, you will become a StarTree & Apache Pinot expert. Additionally, the Enterprise Architect may be called upon to: Support sales efforts (Pre & Post Sales), assist with the development of best practices and processes in a fast changing growth environment, perform training for clients or partners, and perform other duties as needed to run and maintain our business.

Responsibilities

• Ensure a smooth on-boarding process for our customers, including architecture review and best practices for achieving success with our solution.
• Accelerate our customers' Time to Value by being the Technical Subject Matter Expert (SME)
• Work closely with the Customer Success Manager to:
• make sure our customers' requirements are addressed
• discover growth opportunities, threats, and other strategic situations within customer accounts
• Partner with Customer Support and Engineering to help troubleshoot performance and configuration issues for StarTree customers
• Build strong relationship internally by collaborating with Sales, Product & Engineering teams
• Improve Services Offerings by documenting and championing field observations and solutions with Product & Engineering
• Foster and maintains a strong culture of customer service and responsiveness
• Identify and implement changes to methods, processes, systems and technologies to improve customer time to value and satisfaction.

Qualifications

• 3+ years of experience in Pre/Post-Sales or Customer facing roles
• Experience developing or using open-source data technologies
• Experience with modern OLAP systems like Apache Pinot, Druid, Clickhouse is a plus
• Experience with big data technologies such as Spark, Hadoop and Presto / Trino is a plus
• Strong understanding of, and hands on experience with, OLAP, Analytics / SQL
• Experience and/or strong understanding of streaming technologies such as Apache Kafka or Flink
• Excellent communication, presentation, and demonstration skills, as well as a good understanding of the sales and post sales processes
• Strong problem solving and troubleshooting skills (system/application/network/JVM debugging)
• Strong grasp of cloud infrastructure patterns and services in at least one of the three pubic clouds - Amazon AWS, Google Cloud, Microsoft Azure
• Bonus points: Certification in Solutions Architecture in one or more of the three public clouds - Amazon AWS, Google Cloud, Microsoft Azure
• Bonus points: Masters degree in Computer Science with a major in Data related field (Data Science, Data Engineering, or Data Analytics)

What it Takes to Thrive

• A desire to learn and adapt in a rapidly growing and changing environment.
• You must be a self-starter who thrives on complexity and independence.
• Being highly organized and detail-oriented.
• Strong written and oral communication skills.
• Ability to learn quickly. 
• Strong team player.

C3 AI is looking for Senior Software Engineers to join the rapidly growing Data org within the Platform Engineering department. Successful candidates will get the opportunity to work on high-value technologies at the intersection of large-scale distributed systems, data infrastructure, and machine learning. You will design, develop, and maintain various features in a highly scalable and extensible AI/ML platform for large-scale applications, involving data science, distributed systems, and multi-cloud strategy.

You will be given opportunities to take ownership of components, collaborate to drive technical direction, and work on interesting, impactful projects. Join us in building the next-generation AI/ML platform at petabyte level scale that powers some of the world’s largest companies in Energy, Financial Services, Utilities, Health Care, Aerospace, Defense, etc. Accelerate your career in the leading enterprise AI company that is in a hyper-growth trajectory.

Responsibilities:

• Design and develop infrastructure and services to enable data pipelines for petabyte level scale and more.
• Design and develop abstractions over datastores such as Cassandra, PostgreSQL, Snowflake, etc.
• Design and develop file system abstractions over AWS S3, Azure Blobs, HDFS, etc.
• Design and develop connectors to various external data stores.
• Design and develop distributed system components for stream processing, queueing, batch processing, analytics engines, etc.
• Develop and maintain industry-leading, high-performance APIs for AL/ML applications.
• Develop and maintain features for distributed computations over large-scale data for ML workflows.
• Design and develop ML-specific data-systems such as feature stores and behavioral frameworks such as recommendation engines.
• Design and develop integrations with distributed computing technologies such as Apache Spark, Ray, etc. for data exploration and ML workload orchestration.
• Design and develop integrations with data analysis libraries such as Pandas, Koalas, etc.
• Develop and production AI/ML models for failure prediction, data schema inferencing, etc.
• Work on frameworks for performance, scalability, and reliability tracking over different components of a highly extensible AI/ML platform.
• Work with architects, product managers, and software engineers across teams in a highly collaborative environment.
• Participate and provide insights in technical discussions.
• Write clean code following a test-driven methodology.
• Deliver commitments promptly following agile software development methodology.

Qualifications:

• Bachelor of Science in Computer Science, Computer Engineering, or related fields.
• A minimum of 5 years of work experience in a fast-paced software company.
• Strong understanding of Computer Science fundamentals.
• High proficiency in coding with Java, C++, C#, or some other compiled language. Python would also be acceptable.
• Strong competency in object-oriented programming, data structures, algorithms, and software design patterns.
• Experience with version control systems such as Git.
• Experience with large-scale distributed systems.
• Experience with any public cloud platform (AWS, Azure, GCP).
• Some familiarity with distributed computing technologies (e.g., Hadoop, Spark, Kafka). Familiarity with managed versions of these technologies on public cloud platforms is also acceptable.
• Familiarity with technologies in the modern data science/analysis and engineering ecosystem (e.g., Pandas, Koalas).
• Good verbal and written technical communication ability to facilitate collaboration.
• Thrive in a fast-paced, dynamic environment and value end-to-end ownership of components.
• Intellectually curious and open to challenges.

Preferred Qualifications:

• Advanced degree in engineering, sciences, or related field.
• Experience with Agile development methodology.
• Experience developing and working with REST and/or GraphQL APIs.
• Experience building scalable and reliable data pipelines.
• Experience with integration of data from multiple sources.
• Experience working with analytics and/or data processing engines.
• Experience developing distributed computation over large-scale data.
• Experience working with distributed computing frameworks (e.g., Hadoop, Spark, Kafka).
• Experience with data science/analysis libraries (e.g., Pandas, Koalas).
• Experience with task schedulers in distributed computing (e.g., Spark, Ray, Dask).
• Familiarity with machine learning workload orchestration in a distributed computing environment.
• Familiarity with workflow execution and/or optimization using DAGs, ideally for machine learning use-cases.
• Conceptual understanding of orchestration and resource provisioning systems (Kubernetes)

Company Overview

Maven Robotics is building the world’s leading general-purpose AI robots.

We are currently operating in stealth and are growing the world’s best team in AI robotics. We are looking for self-starters that are the world’s best in their field, who can innovate from a deep understanding of the fundamentals, and who share our values of unwavering truth seeking and integrity, humility, curiosity, and relentless determination.

Role Description

We are looking to recruit an exceptional Software Engineer - Software Development and Machine Learning Operations to build and maintain the infrastructure that supports our software development, machine learning models, and AI operations.

In this role you will:

• Design, implement, and manage CI/CD pipelines to facilitate seamless code integration and deployment.
• Monitor and optimize system performance, availability, and security.
• Automate infrastructure orchestration and configuration management using tools such as Kubernetes, Ansible, and similar.
• Configure and maintain data infrastructure appliances.
• Troubleshoot and resolve issues related to applications, infrastructure, and deployments.
• Work closely with our development and AI teams to deliver solutions that increase efficiency and stability.

Qualifications

Must-have:

• BS or MS in software engineering, computer science, or a related field.
• Proven experience standing up a CI/CD system from scratch.
• Experience with multi-language build systems (e.g., Bazel, Bob).
• Proficiency with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).
• Experience with automation tools (e.g., Terraform, Ansible, GitHub Actions, Jenkins) and version control systems (e.g., Git).
• Strong programming skills in languages such as Python, Go, or Java.
• Self-starter attitude with strong ability to identify problems, prioritize them, then plan and execute working solutions.
• Enthusiasm for working in a fast paced startup environment and eagerness to support the team on a variety of topics.

Nice-to-have:

• Experience with MLOps platforms (e.g., MLflow, Kubeflow, or SageMaker).
• Knowledge of big data technologies (e.g., Hadoop, Spark, or Kafka).
• Experience with monitoring and observability tools (e.g., Prometheus, Grafana, ELK stack).
• Understanding of machine learning frameworks (e.g., TensorFlow, PyTorch, or Scikit-Learn).
• Experience with edge computing and IoT device management.
• Knowledge of security best practices and compliance standards in AI/ML environments.
• Proficiency in database management systems (e.g., PostgreSQL, MongoDB, or Cassandra).
• Experience with infrastructure-as-code tools (e.g., CloudFormation, Pulumi).
• Knowledge of GitOps practices and tools (e.g., ArgoCD, Flux).