Reddit has a flexible first workforce. At Reddit we continue to grow our teams with the best talent. We're completely remote friendly and will continue to be after the pandemic.

Advertising is Reddit’s primary revenue driver and we have an ambitious goal to turn it into a massive business. Although several large digital ad platforms already exist, advertisers are being increasingly drawn to Reddit because of our passionate communities. We believe our community-centric platform has created the opportunity for Reddit to build a highly differentiated ads business.

About the Ads Data Science Team:

The Ads Data Science team at Reddit leverages data to maximize advertiser value on Reddit through robust data foundations, metrics, and strategic insights generated through experimentation and cutting-edge DS methods. 

We work on a wide range of challenging problems in the areas of ads targeting, relevance modeling, auction optimization, measurement, and user experience. We are a highly collaborative team of passionate data scientists and engineers who are constantly pushing the boundaries of what's possible with machine learning and statistical modeling.

About the Role:

We are looking for a highly motivated and experienced Data Scientist to join our growing Ads Data Science team. As a Data Scientist, you will play a key role in developing as well as applying cutting-edge DS models/methods to improve our understanding of the dynamics that drive the success of our advertising platform, and identify opportunities to accelerate that success. You will work closely with stakeholders across product, engineering, sales, marketing, and data to identify opportunities, define metrics, and build solutions that drive significant impact for Reddit.

Responsibilities:

• Analyze large-scale datasets to identify trends, patterns, and insights that can be used to improve the effectiveness of our advertising platform
• Develop ML models & DS methods to for improved anomaly detection, prediction, pattern recognition
• Communicate findings and recommendations to stakeholders across the organization
• Collaborate with product, engineering, sales, and marketing partners to define product and program requirements and translate them into data science solutions
• Stay up-to-date on the latest advancements in machine learning and data science

Qualifications:

• Advanced degree (Masters or Ph.D.) in a quantitative field such as: Statistics, Mathematics, Physics, Economics, or Operations Research
• For M.S. holders: 3+ years of industry experience in applied science or data science roles
• For Ph.D. holders: 2+ years of industry experience in applied science or data science roles
• Strong understanding of statistical modeling, machine learning algorithms, causal inference and experimental design
• Experience with large-scale data processing and analysis using tools such as Spark, Hadoop, or Hive; knowledge of BigQuery a plus
• Proficiency in Python or R and experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch
• Experience with SQL and relational databases
• Excellent communication and presentation skills
• Passion for Reddit and the online advertising industry

Bonus Points:

• Experience with online advertising and ad tech
• Experience with causal inference and A/B testing
• Contributions to open-source projects or publications in relevant conferences or journals

Benefits:

• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Comprehensive Medical Benefits & Health Care Spending Account
• Registered Retirement Savings Plan with matching contributions
• Income Replacement Programs
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave

#LI-Remote

Reddit has a flexible first workforce. At Reddit we continue to grow our teams with the best talent. We're completely remote friendly and will continue to be after the pandemic.

Advertising is Reddit’s primary revenue driver and we have an ambitious goal to turn it into a massive business. Although several large digital ad platforms already exist, advertisers are being increasingly drawn to Reddit because of our passionate communities. We believe our community-centric platform has created the opportunity for Reddit to build a highly differentiated ads business.

About the Ads Data Science Team:

The Ads Data Science team at Reddit leverages data to maximize advertiser value on Reddit through robust data foundations, metrics, and strategic insights generated through experimentation and cutting-edge DS methods. 

We work on a wide range of challenging problems in the areas of ads and platform measurement, campaign and creative management, advertiser growth and retention, monetization, and the intersection of brand and community engagement. We are a highly collaborative team of passionate data scientists and engineers who are constantly pushing the boundaries of what's possible with machine learning and statistical modeling.

About the Role:

We are looking for a highly motivated and experienced Senior Data Scientist to join our growing Ads Data Science team. As a Senior Data Scientist, you will play a key role in developing as well as applying cutting-edge DS models/methods to improve the adoption and performance of our advertising platform through data-driven insights. You will work closely with product managers, engineers, and other data scientists to identify opportunities, define metrics, and build solutions that drive significant impact for Reddit.

Responsibilities:

• Design, develop, and apply DS solutions to inform improvements in advertiser experience and Reddit's ad platform
• Analyze large-scale datasets to identify trends, patterns, and insights that can be used to improve the effectiveness of our advertising platform
• Collaborate with product managers and engineers to define product requirements and translate them into data science solutions
• Develop ML models & DS methods to improve anomaly detection, prediction, & pattern recognition 
• Communicate findings and recommendations to stakeholders across the organization
• Stay up-to-date on the latest advancements in machine learning and data science
• Mentor and guide junior data scientists on the team

Qualifications:

• Advanced degree (Masters or Ph.D.) in a quantitative field such as: Statistics, Mathematics, Physics, Economics, or Operations Research
• For M.S. holders: 5+ years of industry experience in applied science or data science roles
• For Ph.D. holders: 4+ years of industry experience in applied science or data science roles
• Platform experience and a deep understanding of the ads ecosystem
• Strong understanding of statistical modeling, machine learning algorithms, causal inference and experimental design
• Experience with large-scale data processing and analysis using tools such as Spark, Hadoop, or Hive; knowledge of BigQuery a plus
• Proficiency in Python or R and experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch
• Experience with SQL and relational databases
• Excellent communication and presentation skills
• Passion for Reddit and the online advertising industry

Bonus Points:

• Experience with online advertising and ad tech
• Experience with causal inference and A/B testing
• Contributions to open-source projects or publications in relevant conferences or journals

Benefits:

• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Comprehensive Medical Benefits & Health Care Spending Account
• Registered Retirement Savings Plan with matching contributions
• Income Replacement Programs
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave

#LI-Remote

About the Role:

We are seeking an experienced Principal Software Engineer (Data) to join our fast-paced, collaborative data team. In this role, you will have broad authority to drive the direction of our technographic data services, building world-class data pipelines and systems to process billions of signals and data points. This is an exciting opportunity to solve challenging problems and make a big impact as we invest in making technographics a first-class offering.

What You'll Do:

• Build and optimize big data pipelines to extract and process signals from the web, job postings, and other sources
• Design and implement data architectures and storage solutions to efficiently handle massive data volumes
• Collaborate closely with data scientists to support and integrate ML models into data workflows
• Continuously improve data quality, performance, and scalability of our technographic data platform
• Drive technical strategy and roadmap for the data processing infrastructure.

What We're Looking For:

• Extensive experience building and scaling big data pipelines and architectures from scratch
• Deep expertise in big data frameworks (Hadoop, Spark) and the JVM stack (Java, Scala)
• Strong software engineering fundamentals and ability to write efficient, high-quality code
• Experience with entity recognition and NLP techniques a plus
• Proven track record delivering results and driving projects in a fast-paced environment
• Excellent collaboration and communication skills to work with data scientists, analysts and product teams
• Passion for leveraging huge datasets to power valuable insights.

Ideal Background:

• 10+ years of experience in software engineering roles.
• Experience working with very large datasets and distributed systems
• Familiarity building data pipelines at large tech companies or data-driven organizations
• Bachelor's or advanced degree in Computer Science, Engineering or related technical field.

#LI-SK1

#LI-Remote

Role Description

We're looking for a Data Scientist to partner with product, engineering, and design teams to answer key questions about how to grow revenue, optimize product, scale and monetize the business, and launch high-impact initiatives. We solve challenging problems and boost business growth through a deep understanding of user behaviors with applied analytics techniques and business insights. An ideal candidate should have robust knowledge of consumer lifecycle and behavior analysis, customer segmentation, digital campaigns, monetization analytics and business operations for a SaaS company.  

Responsibilities

• Develop a deep understanding of customer journey phases and key business metrics
• Perform analytical deep-dives to analyze problems and opportunities, identify the hypothesis and design & execute experiments
• Inform future experimentation design and roadmaps by performing exploratory analysis to understand user engagement behavior and derive insights
• Create personalized segmentation strategies leveraging propensity models to enable targeting of offers and experiences based on user attributes 
• Identify key trends and build automated reporting & executive-facing dashboards to track the progress of acquisition, monetization, and engagement trends. 
• Extract actionable insights through analyzing large, complex, multi-dimensional customer behavior data sets 
• Monitor and analyze a high volume of experiments designed to optimize the product for user experience and revenue & promote best practices for multivariate experiments
• Translate complex concepts into implications for the business via excellent communication skills, both verbal and written
• Understand what matters most and prioritize ruthlessly
• Work with cross-functional teams (including Data Science, Marketing, Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate

Requirements

• Bachelors’ or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
• 3-5 years experience using analytics to drive key business decisions; examples include business/product/marketing analytics, business intelligence, strategy consulting
• Proven track record of being able to work independently and proactively engage with business stakeholders with minimal direction
• Significant experience with SQL and large unstructured datasets such as Hadoop
• Deep understanding of statistical analysis, experimentation design, and common analytical techniques like regression, decision trees
• Solid background in running multivariate experiments to optimize a product or revenue flow
• Strong verbal and written communication skills
• Proficiency in programming/scripting and knowledge of statistical packages like R or Python is a plus

Role Description

We're looking for a Data Scientist to partner with product, engineering, and design teams to answer key questions about how to grow revenue, optimize product, scale and monetize the business, and launch high-impact initiatives. We solve challenging problems and boost business growth through a deep understanding of user behaviors with applied analytics techniques and business insights. An ideal candidate should have robust knowledge of consumer lifecycle and behavior analysis, customer segmentation, digital campaigns, monetization analytics and business operations for a SaaS company.  

Responsibilities

• Develop a deep understanding of customer journey phases and key business metrics
• Perform analytical deep-dives to analyze problems and opportunities, identify the hypothesis and design & execute experiments
• Inform future experimentation design and roadmaps by performing exploratory analysis to understand user engagement behavior and derive insights
• Create personalized segmentation strategies leveraging propensity models to enable targeting of offers and experiences based on user attributes 
• Identify key trends and build automated reporting & executive-facing dashboards to track the progress of acquisition, monetization, and engagement trends. 
• Extract actionable insights through analyzing large, complex, multi-dimensional customer behavior data sets 
• Monitor and analyze a high volume of experiments designed to optimize the product for user experience and revenue & promote best practices for multivariate experiments
• Translate complex concepts into implications for the business via excellent communication skills, both verbal and written
• Understand what matters most and prioritize ruthlessly
• Work with cross-functional teams (including Data Science, Marketing, Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate

Requirements

• Bachelors’ or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
• 3-5 years experience using analytics to drive key business decisions; examples include business/product/marketing analytics, business intelligence, strategy consulting
• Proven track record of being able to work independently and proactively engage with business stakeholders with minimal direction
• Significant experience with SQL and large unstructured datasets such as Hadoop
• Deep understanding of statistical analysis, experimentation design, and common analytical techniques like regression, decision trees
• Solid background in running multivariate experiments to optimize a product or revenue flow
• Strong verbal and written communication skills
• Proficiency in programming/scripting and knowledge of statistical packages like R or Python is a plus

Role Description

We're looking for a Data Scientist to partner with product, engineering, and design teams to answer key questions about how to grow revenue, optimize product, scale and monetize the business, and launch high-impact initiatives. We solve challenging problems and boost business growth through a deep understanding of user behaviors with applied analytics techniques and business insights. An ideal candidate should have robust knowledge of consumer lifecycle and behavior analysis, customer segmentation, digital campaigns, monetization analytics and business operations for a SaaS company.  

Responsibilities

• Develop a deep understanding of customer journey phases and key business metrics
• Perform analytical deep-dives to analyze problems and opportunities, identify the hypothesis and design & execute experiments
• Inform future experimentation design and roadmaps by performing exploratory analysis to understand user engagement behavior and derive insights
• Create personalized segmentation strategies leveraging propensity models to enable targeting of offers and experiences based on user attributes 
• Identify key trends and build automated reporting & executive-facing dashboards to track the progress of acquisition, monetization, and engagement trends. 
• Extract actionable insights through analyzing large, complex, multi-dimensional customer behavior data sets 
• Monitor and analyze a high volume of experiments designed to optimize the product for user experience and revenue & promote best practices for multivariate experiments
• Translate complex concepts into implications for the business via excellent communication skills, both verbal and written
• Understand what matters most and prioritize ruthlessly
• Work with cross-functional teams (including Data Science, Marketing, Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate

Requirements

• Bachelors’ or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
• 3-5 years experience using analytics to drive key business decisions; examples include business/product/marketing analytics, business intelligence, strategy consulting
• Proven track record of being able to work independently and proactively engage with business stakeholders with minimal direction
• Significant experience with SQL and large unstructured datasets such as Hadoop
• Deep understanding of statistical analysis, experimentation design, and common analytical techniques like regression, decision trees
• Solid background in running multivariate experiments to optimize a product or revenue flow
• Strong verbal and written communication skills
• Proficiency in programming/scripting and knowledge of statistical packages like R or Python is a plus

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. 

The Safety and Customer Care (SCC) team at Lyft manages over 1.7 million monthly human and AI interactions and serves as Lyft's primary direct touchpoint with riders and drivers. We handle critical infrastructure that powers both human associates and AI agents to make riders and drivers feel safe and comfortable while riding or driving with Lyft, transforming every support interaction into a moment of genuine connection. 

As a Data Engineer on the SCC team, you will have ownership over the data modeling and pipelines that power SCC’s Associate and AI Agent Platform . Your efforts will be critical to the reliability of our pipelines, execution of third party data integrations, accurate reporting of agents performance, and efficiency improvements that can save millions of dollars / year. You will work cross-functionally to bridge Lyft's business goals with data engineering. Your efforts will allow access to business and user behavior insights, using huge amounts of Lyft data to fuel several teams such as Analytics, Data Science, Engineering, and many others. 

Responsibilities:

• Owner of the core data pipeline, responsible for scaling up data processing flow to meet the rapid data growth at Lyft
• Evolve data model and data schema based on business and engineering needs
• Implement systems tracking data quality and consistency
• Develop tools supporting self-service data pipeline management (ETL)
• SQL and MapReduce job tuning to improve data processing performance
• Write well-crafted, well-tested, readable, maintainable code
• Participate in code reviews to ensure code quality and distribute knowledge
• Collaborate cross-functionally with product, engineering, data science, and marketing teams to understand business problems and align on prioritization and solutions

Experience:

• Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field
• 4+ years of professional experience in data engineering, ideally with large-scale distributed systems.
• Strong skills in Spark, Python (or similar scripting language), and SQL performance tuning
• Experience with AWS, Hadoop/S3, Hive, Presto, Airflow, and related tools
• Solid understanding of ETL processes, workflow orchestration, and data warehousing
• A collaborative mindset—you’re comfortable working across teams to solve real-world problems

Benefits:

• Extended health and dental coverage options, along with life insurance and disability benefits
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• Access to a Lyft funded Health Care Savings Account
• RRSP plan with company match to help save for your future
• In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service 
• Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible.
• Subsidized commuter benefits and Lyft ride credits

Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind.  Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter if you wish to make such a request.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the Toronto area is CAD $108,000 - CAD $135,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.

This job fills an existing vacancy.

The Mission

We are seeking an Engineering Manager for our Cloud Data Engineering Practice. The right candidate is someone who is technically strong, can manage a team of Architects and Engineers, oversee data delivery engagements and is passionate about working with our customers, partners and employees to drive the business forward.

Your Assignment

• Manage a team of 5 - 8 cloud engineers and architects
• Interface with clients and internal teams to propose technical improvements using your cloud and engineering knowledge
• Take on hands-on technical responsibilities, including technical tasks in sprints 
• Lead technical discussions with customers
• Handle code reviews and pull request management
• Manage task assignments within sprints
• Perform technical leadership activities like roadmap and vision checks, best practices implementation, and risk identification
• In-project mentoring (understand people on project & creation of growth opportunities) and sharing feedback for team members on the project
• Technical accountability on the delivery
• Kickoff new client engagements and act as a point of technical escalation
• Develop and review proposals and contracts and present these to clients
• Perform technical interviews for Architect and Engineer candidates
• Perform weekly 1:1s with your direct reports and guide their career development
•  

Your Qualifications

• Strong experience in AWS data landscape
• Expertise in at least two major areas of Cloud Data Engineering:
  • Relational database design, optimization and migration
  • Big data processing using Spark, Hadoop, EMR etc
  • Machine Learning and MLOps
  • Advanced analytics using time series forecasting, descriptive and inferential statistics
  • BI dashboards and visualizations
  • Data Governance and MDM
• Experience with most of these:
  • Infrastructure as Code tools
  • CI/CD pipelines
  • Application modernization and migration with a strong focus on databases
• Excellent written and verbal communication skills

Benefits

• 100% remote work
• Equitable Life - Hybrid Plan
• 100% Premium Coverage for the employee and dependents
• Competitive phantom equity
• Long-Term Disability
• 4% Pension match (employer contribution)
• Unlimited Vacations
• Sick Leave 
• Paid Holidays 
• Parental Leave
• Paid for exams and certifications
• Peer bonus awards
• State of the art laptop and tools
• Equipment & Office Stipend
• Individual professional development plan
• Annual stipend for Learning and Development
• Work with an amazing worldwide team and in an incredible corporate culture

Base Salary Range: The expected base salary range for this position is CAD $152,000 - $193,000 per year, commensurate with experience and qualifications.

Additional Compensation Components: In addition to the base salary, the compensation package may include bonuses, commissions, equity, and other incentives. The specific components will vary depending on the role and individual and/or company performance.

Caylent is a place where everyone belongs.  We celebrate diversity and are committed to creating an inclusive environment for all employees. Our approach helps us to build a winning team that represents a variety of backgrounds, perspectives, and abilities. So, regardless of how your diversity expresses itself, you can find a home here at Caylent.   

We are proud to be an equal opportunity employer. We prohibit discrimination and harassment of any kind based on race, color, religion, national origin, sex (including pregnancy), sexual orientation, gender identity, gender expression, age, veteran status, genetic information, disability, or other applicable legally protected characteristics. If you would like to request an accommodation due to a disability, please contact us at hr@caylent.com. 

While candidates in the listed locations are encouraged for this role, we are open to remote candidates in other locations in Canada

Location: Montreal, QC

As a 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 which 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 customer's needs and 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:

• 5+ years in a customer-facing pre-sales, technical architecture, 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.

Location: Ottawa, ON

As a Solutions Architect on the Canada team focused on Digital Native customers, 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.
• 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
• 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.

Overview

Are you ready to take your development skills to the next level? We’re looking for a Senior Software Engineer to join our Ads team. You’ll play a critical role in the evolution of our Ads suite and help build world-class reporting solutions across various platforms, ensuring that advertisers and retailers receive timely, accurate, and actionable data insights. By working closely with Product Designers, Product Managers, Data Scientists, Machine Learning Engineers, and other cross-functional partners, you’ll contribute to the advancement of our Ads suite and guarantee a seamless flow of data to our users.

The Instacart Ads team is at the forefront of refining our Ads products and supporting infrastructure, so your work will directly enhance our capability to process petabyte-scale data and deliver reports essential for billing, strategic decision-making, and partner management.

Our products are used by millions of people every year. To meet–and exceed–expectations we are rapidly improving and modernizing our ads platform, helping raise the quality bar for our products across the entire organization. Sound exciting? Keep reading.

The Ads team is a diverse group of spirited and highly-dedicated engineers focused on crafting and delivering comprehensive reporting solutions to our advertisers and retailers.

Our team thrives on dynamic challenges, and we take pride in developing and maintaining scalable and fault-tolerant metrics delivery systems. We've embraced a culture of open and candid collaboration where everyone's views matter, allowing us to continuously innovate and make substantial impact to the digital advertising industry through our work.

Our tech stack includes but is not limited to Rails, Go, DBT, Airflow, Scala, Apache Spark, Databricks, Delta Lake, Snowflake, Python and Terraform. We believe in constantly learning, growing and adopting the most efficient practices that enable us to deliver quality data services to our stakeholders. If you're a detective at heart, love solving complex problems, and are passionate about the intersection of data and technology, you'll fit right in!

Overview of the Ads teams that are currently hiring: 

• Ads Measurement & Data: Our cutting-edge data team is responsible for building scalable, reliable, and maintainable ETLs and its underlying architecture and platform. We directly support critical internal and external systems and metrics such as billing, attribution, spam detection, etc. Our non-functional requirements are achieved through streaming and batch processing using Scala-Spark, Airflow, DBT, Python, and Go. If you're interested in working cross-functionally with several key stakeholders, helping shape our data strategy, building distributed systems, and solving complex data architecture challenges in a fast-paced, high-impact environment, this could be the opportunity for you!

• Advertiser Optimization: We power Instacart’s advertising business by creating innovative solutions that maximize ad performance and deliver measurable value to our partners. Through advanced algorithms, machine learning, and a robust data ecosystem, the team helps advertisers achieve their goals while driving Instacart’s revenue growth. By fostering a cycle of success for advertisers, they play a pivotal role in the company’s overall business success.

About the Job

We believe that high-quality data is essential for any business organization, as such we are looking for a strong software engineer excited to raise our efficiency, quality and scalability bar. You will be able to have extensive ownership and the ability to help set best practices and contribute to product and infrastructure features. 

As a craft leader, you'll be responsible for contributing to the vision, strategy and development of our multi-platform reporting system that is efficient, scalable, and meets diverse user needs. You will advocate for data quality, correctness, scalability and latency standards to ensure consistency in how we enable data-driven decisions and features across the organization. 

You will also be proactive in spearheading new initiatives, coding and documenting components, writing and reviewing system design documents and partnering with other teams and functions to gather and understand our customer's requirements. You will think and plan strategically for short and long term initiatives to continue shaping our platform and products.

About You

Minimum Qualifications

• Bachelor's degree or higher in Computer Science, Software Engineering, or a related field, or equivalent proven industry experience (4+ years).
• 5+ years of experience in software engineering.
• Comprehensive understanding of distributed systems, proven experience with data processing technologies such as DBT and Airflow and common web frameworks such as Rails.
• Highly proficient with SQL, capable of writing and reviewing complex queries for data analysis and debugging.
• You can design for scale with the entire system in mind.
• Solid communicator, comfortable seeking and receiving feedback.
• Strong analytical and debugging skills.
• Strong sense of ownership working with a large codebase and diverse suite of products.
• A collaborative mindset to be able to partner with engineers, designers and PM's from multiple teams to co-create impactful solutions while supporting system contributions.
• Strong organizational skills with the ability to communicate and present ideas clearly and influence key stakeholders at the manager, director, and VP level.

Preferred Qualifications

• Prior work experience in the digital advertising industry.
• Experience with big data technologies such as Spark, Hadoop, Flink, Hive or Kafka, and with both streaming and batching data pipelines.
• Proven experience with distributed system design.
• Strong general programming and algorithm skills.
• Strong attention to detail and accuracy in the implementation, keen eye for edge cases and code reviews. 
• Data driven mindset.

#LI-Remote

P-225

While candidates in the listed locations are encouraged for this role, we are open to remote candidates in other locations in eastern Canada

As a 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 which 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 customer's needs and 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:

• 5+ years in a customer-facing pre-sales, technical architecture, 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.

The Role

We are seeking a Senior AI Engineer to join our AI & Data Group on the AI Orchestration team. This role is responsible for designing, building, operating and scaling the orchestration layer that powers League’s AI-driven healthcare experiences. 

Sitting at the intersection of AI systems design, ML productionization, and distributed software engineering, you will take the probabilistic capabilities of large language models and engineer them into reliable, measurable, and scalable product experiences.

This is a hands-on senior engineering role for a practitioner who moves beyond prototypes to own the hard problem of making AI work at scale. You will translate leading edge AI innovation into reliable, secure, and compliant systems. Your work will directly impact how AI is operationalized across League’s digital health ecosystem—ensuring systems are scalable, observable, performant, and safe in a regulated environment.

How You'll Make an Impact:

As a Staff Data Engineer, you'll design and implement large-scale distributed data processing systems using technologies like Apache Hadoop, Spark, and Flink. You'll build robust data pipelines and infrastructure that transform complex data into actionable insights, ensuring scalability and fault-tolerance across our platform that processes billions in bookings annually.

You'll architect data lakes, warehouses, and real-time streaming platforms while implementing security measures and optimizing performance. With your expertise in distributed computing, containerization (Docker, Kubernetes), and streaming technologies (Kafka, Confluent), you'll drive innovation and evaluate new technologies to continuously improve our data ecosystem.

Our Data team:

We're energized by turning complex, messy data into meaningful insights that drive real impact across the organization. As a team, we thrive on solving data infrastructure challenges at scale, building resilient pipelines, optimizing performance, and architecting systems that enable everyone from analysts to executives to make smarter, faster decisions.

What sets us apart is our culture of deep trust and collaboration. No one gets left stuck. When someone hits a blocker, the team jumps in to help without hesitation. We're problem solvers with a shared mission, where collaboration isn't just encouraged, it's expected, and collective wins matter more than individual credit.

What You Bring to the Team:

• Technical Expertise & Scalability Mindset
  Deep knowledge of data architecture, ETL/ELT pipelines, and distributed systems, with the ability to design scalable, high-performance solutions.
• Problem-Solving & Ownership
  A proactive approach to diagnosing issues, improving infrastructure, and taking full ownership from concept to production.
• Code Quality & Best Practices
  Strong skills in writing clean, maintainable code (e.g., in Python, SQL, or Scala) and championing best practices like version control, testing, and CI/CD for data.
• Collaboration & Mentorship
  The ability to work cross-functionally with analysts, data scientists, and engineers, while mentoring junior team members and raising the team’s technical bar.
• Data Governance & Reliability Focus
  A strong sense of responsibility for data accuracy, lineage, and security—building systems that others can trust and scale on.

What Sets You Up for Success:

• Clear Business Context
  Understanding the “why” behind data needs—when goals and use cases are clear, it’s easier to design impactful and relevant solutions.
• Autonomy with Trust
  The freedom to make technical decisions, explore solutions, and iterate—paired with the trust that you’ll deliver with quality and accountability.
• Strong Team Collaboration
  Being part of a team that shares knowledge openly, helps each other unblock challenges, and values collective wins over individual credit.
• Access to Quality Tooling & Infrastructure
  Having the right modern tools (e.g., Airflow, dbt, Spark, Flink, cloud platforms) and the ability to improve them when needed sets the foundation for effective work.
• Supportive Leadership & Growth Mindset
  Managers who advocate for your growth, give regular feedback, and create space for learning and experimentation help sustain long-term success.

Bonus Skills to Stand Out (Optional):

• Leadership skills: guiding and mentoring junior members, coordinating projects and collaborating with other teams.
• Domain Knowledge: Having understanding of the hospitality industry can greatly enhance your ability to design and build effective data pipelines.
• Data Architecture Expertise: Contributing to designing data architecture and system and having deep understanding of data storage and ability to design a robust, scalable and maintainable architecture is a valuable skill.
• Performance Optimization: Being able to optimize the performance of data pipelines is a crucial skill such as query optimization, indexing, caching and data partitioning.
• Programming knowledge: Knowledge of Python and SQL is essential, familiarity with Java and other languages is a plus.
• Experience working with a remote-first and globally distributed team
• Experience with CI/CD tooling, including GitHub Actions and Build Workflows
• Knowledge of Confluent and AWS

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