About the Team

The Analytics Engineering team at DoorDash is embedded within the Analytics and Data Engineering Orgs, and is responsible for building internal data products that scale decision-making across business teams and drive efficiency in our operations. Data is fundamental to DoorDash’s success, and this team plays a critical role in enabling high-impact, data-driven solutions across Product, Operations, Finance, and more.

About the Role

As an Analytics Engineer, you’ll play a key role in building and scaling the data foundations that enable fast, reliable, and actionable insights. You’ll work closely with partner teams to drive end-to-end analytics initiatives; working alongside Data Engineers, Data Scientists, Software Engineers, Product Managers, and Operators.

This is a highly technical role where you'll be a driving force behind the analytics stack, delivering trusted data and metrics that support decision-making at all levels of the company. If you're energized by solving technical problems with data and comfortable being deeply embedded across several domains, this role is for you!

You’re excited about this opportunity because you will…

• Collaborate with data scientists, data engineers, and business stakeholders to understand business needs, and translate that scope into data requirements
• Identify key business questions and problems to solve for, and generate insights by developing structured solutions to resolve them
• Lead the development of data products and self-serve tools that enable analytics to scale across the company
• Build and maintain canonical datasets by developing high-volume, reliable ETL/ELT pipelines using data lake and data warehousing concepts
• Design metrics and data visualizations with dashboarding tools like Tableau, Sigma, and Mode
• Be a cross-functional champion at upholding high data integrity standards to increase reusability, readability and standardization

We’re excited about you because…

• 5+ years of experience working in business intelligence, analytics engineering, data engineering, or a similar role
• Strong proficiency in SQL for data transformation, comfort in at least one functional/OOP language such as Python or Scala
• Expertise in creating compelling reporting and data visualization solutions using dashboarding tools (e.g., Looker, Tableau, Sigma)
• Familiarity with database fundamentals (e.g., S3, Trino, Hive, Spark), and experience with SQL performance tuning
• Experience in writing data quality checks to validate data integrity (e.g., Pydeequ, Great Expectations)
• Excellent communication skills and experience working with technical and non-technical teams
• Comfortable working in fast fast-paced environment, self-starter, and self-organizer
• Ability to think strategically, analyze, and interpret market and consumer information

Nice to Have

• Experience with modern data warehousing platforms (e.g., Snowflake, Databricks, Redshift) and ability to optimize performance
• Experience building multi-step ETL jobs coupled with orchestrating workflows (e.g. Airflow, Dagster, DBT)
• Familiarity with experimentation concepts like A/B testing and their data requirements

Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only

We use Covey as part of our hiring and/or promotional process for jobs in NYC and certain features may qualify it as an AEDT in NYC. As part of the hiring and/or promotion process, we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound from August 21, 2023, through December 21, 2023, and resumed using Covey Scout for Inbound again on June 29, 2024.

The Covey tool has been reviewed by an independent auditor. Results of the audit may be viewed here: Covey

About the Team

Data is at the foundation of DoorDash success. The Data Engineering team builds database solutions for various use cases including reporting, product analytics, marketing optimization and financial reporting. By implementing pipelines, data structures, and data warehouse architectures; this team serves as the foundation for decision-making at DoorDash.

About the Role

DoorDash is looking for a Senior Data Engineer to be a technical powerhouse to help us scale our data infrastructure, automation and tools to meet growing business needs.

You're excited about this opportunity because you will…

• Work with business partners and stakeholders to understand data requirements
• Work with engineering, product teams and 3rd parties to collect required data
• Design, develop and implement large scale, high volume, high performance data models and pipelines for Data Lake and Data Warehouse
• Develop and implement data quality checks, conduct QA and implement monitoring routines
• Improve the reliability and scalability of our ETL processes
• Manage a portfolio of data products that deliver high-quality, trustworthy data
• Help onboard and support other engineers as they join the team

We're excited about you because…

• 5+ years of professional experience
• 3+ years experience working in data engineering, business intelligence, or a similar role
• Proficiency in programming languages such as Python/Java
• 3+ years of experience in ETL orchestration and workflow management tools like Airflow, Flink, Oozie and Azkaban using AWS/GCP
• Expert in Database fundamentals, SQL and distributed computing
• 3+ years of experience with the Distributed data/similar ecosystem (Spark, Hive, Druid, Presto) and streaming technologies such as Kafka/Flink.
• Experience working with Snowflake, Redshift, PostgreSQL and/or other DBMS platforms
• Excellent communication skills and experience working with technical and non-technical teams
• Knowledge of reporting tools such as Tableau, Superset and Looker
• Comfortable working in fast paced environment, self starter and self organizing
• Ability to think strategically, analyze and interpret market and consumer information
• You must be located near one of our engineering hubs indicated above

Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only

We use Covey as part of our hiring and/or promotional process for jobs in NYC and certain features may qualify it as an AEDT in NYC. As part of the hiring and/or promotion process, we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound from August 21, 2023, through December 21, 2023, and resumed using Covey Scout for Inbound again on June 29, 2024.

The Covey tool has been reviewed by an independent auditor. Results of the audit may be viewed here: Covey

Staff Analytics Engineer

Location: Hyderabad | Department: Technology, Data

About the Role

Are you passionate about turning raw data into actionable insights and enabling data-driven decision-making? As an Analytics Engineer, you will play a critical role in shaping our data ecosystem and ensuring that our teams have access to accurate, well-structured, and timely insights.

You’ll collaborate closely with different business functions to design and implement scalable data models, track key performance metrics, and optimize data workflows. Your work will directly impact how we measure product success, marketing effectiveness, and customer engagement.

What You'll Do

Collaboration & Enablement

• Act as the Technical Lead for the team, taking ownership of our engineering standards and driving the rigorous application of best practices in data and semantic modeling.
• Partner with cross-functional teams to democratize data access and improve self-serve analytics capabilities.
• Partner with cross-functional teams to gather requirements and implement reporting/dashboards which allow those teams to improve performance
• Create and maintain clear documentation for data models, metrics, and best practices.

Data Engineering & Pipeline Optimization

• Use dbt (Data Build Tool) to build, test, and optimize scalable data models.
• Implement semantic models within our Business Intelligence platform
• Implement reports/dashboards in our Business Intelligence platform which leverage our semantic model
• Work with cloud data warehouses (BigQuery, Snowflake, or Redshift) to ensure efficient data transformation and storage.
• Implement automated data quality checks to maintain integrity and reliability across datasets.

What You’ll Need

Technical Skills & Experience

• 7+ years of experience in analytics engineering
• Strong SQL skills and experience working with data warehouses (BigQuery, Snowflake, or Redshift).
• Strong reporting/dashboarding skills leveraging a modern Business Intelligence platform with a Semantic Layer (Omni, Looker, Lightdash)
• Hands-on experience with dbt for data modelling and transformation.

Soft Skills & Collaboration

• Ability to work cross-functionally with different stakeholders.
• Excellent problem-solving skills and a structured approach to data challenges.
• Strong written and verbal communication skills to translate complex data concepts for non-technical stakeholders.
• Self-motivated and eager to optimize and automate data processes wherever possible.

Why Join Us?

We welcome people from all backgrounds who seek the opportunity to help build a future where we connect the dots for international property payments. If you have the curiosity, passion, and collaborative spirit, work with us, and let’s move the world of PropTech forward, together.

Redpin, Currencies Direct and TorFX are proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, colour, religion, national origin, disability, protected veteran status, age, or any other characteristic protected by law.

Senior Data (Platform) Engineer 

Location: Hyderabad | Department: Technology, Data 

About the Role 

Are you passionate about building reliable, scalable data platforms that make analytics and AI development easier? As a Senior Data Platform Engineer, you will be hands-on in building, operating, and improving our core data platform and AI/LLM enablement tooling. 

You’ll focus on infrastructure, orchestration, CI/CD, and reusable frameworks that support analytics engineering and AI-driven use cases. You’ll work closely with Analytics Engineering and Insights teams and support other departments as they integrate with our data systems. 

What You'll Do 

Data Platform & Infrastructure

• Build, deploy, and operate cloud infrastructure for data and AI workloads using Infrastructure as Code (Terraform).
• Provision and manage cloud resources across development, staging, and production environments.
• Develop and maintain CI/CD pipelines for data transformations, orchestration workflows, and platform services.
• Operate and scale containerized workloads on Kubernetes, including Airflow, internal APIs, and AI/LLM services.
• Troubleshoot and resolve infrastructure, pipeline, and orchestration failures to ensure platform reliability.
• Maintain and support existing ML services and pipelines to ensure stability and reliability (No expectation to design or develop new ML models or training pipelines).
• Continuously monitor and optimize platform performance and cost. 

Framework, Tooling and Enablement

• Build and maintain reusable frameworks and patterns for dbt, Airflow, Cloud data warehouses (Snowflake, BigQuery, Redshift, Databricks, etc.), Internal data and AI APIs
• Build and support infrastructure and pipelines for AI/LLM-based use cases, including orchestration, integration, and serving.
• Improve developer experience for Analytics Engineering and Insights teams by reducing friction in local development, deployments, and production workflows.
• Create and maintain technical documentation and examples to support self-service analytics and data development. 

What You’ll Need 

Technical Skills & Experience

• 5+ years of experience in data engineering, platform engineering, or similar hands-on roles.
• Strong programming skills in Python and SQL.
• Hands-on experience with:
  • Terraform
  • Airflow
  • dbt
  • Kubernetes
  • Cloud platforms (AWS, Google Cloud, or Microsoft Azure)
  • CI/CD pipelines (GitHub Actions, GitLab CI, CircleCI, etc.)
  • Cloud data warehouses (Snowflake, BigQuery, Redshift, Databricks, etc.) 
• Strong understanding of analytical data models and how analytics teams consume data.
• Experience integrating and operating LLM-based pipelines and services (not model training). 

Soft Skills & Collaboration

• Strong problem-solving skills and ability to debug complex platform issues.
• Strong preference for declarative development, with the ability to clearly separate what a system should do from how it is implemented.
• Clear communicator who can work effectively with both technical and non-technical stakeholders.
• Pragmatic, ownership-driven mindset with a focus on reliability and simplicity. 

Why Join Us? 

We welcome people from all backgrounds who seek the opportunity to help build a future where we connect the dots for international property payments. If you have the curiosity, passion, and collaborative spirit, work with us, and let’s move the world of PropTech forward, together. 

Redpin, Currencies Direct and TorFX are proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, colour, religion, national origin, disability, protected veteran status, age, or any other characteristic protected by law.

About the Role

We are seeking a Marketing Science Analyst II to join our Marketing Analytics team in Hyderabad. In this role, you will partner with paid media, growth, and cross-functional teams to measure and optimize marketing performance across digital and offline channels. You will play a key role in campaign measurement, attribution, experimentation, and reporting—translating complex data into actionable insights that drive business growth.

This position is ideal for a highly analytical professional with hands-on marketing analytics experience who is ready to take ownership of measurement frameworks while collaborating across a global organization.

Responsibilities

Campaign Measurement & Attribution

• Support the tracking and reporting of campaign performance by compiling relevant KPIs and spend data. 
• Assist in incrementality testing efforts and contribute to A/B test setup and execution for marketing initiatives. 
• Help evaluate performance using MMM inputs, basic channel lift analysis, and cross-channel measurement frameworks.

Performance Analytics & Optimization

• Track and report key performance metrics including Signups, CAC, CPFT, and payback periods.
• Conduct deep-dive analyses to identify performance drivers and optimization opportunities.
• Assist in maintaining regular campaign reporting across lines of business.
• Develop and refine audience segments for targeted paid campaigns, leveraging data insights to enhance performance

Data Analysis & Reporting

• Write complex SQL queries to analyze large datasets (millions to billions of records).
• Build and maintain dashboards in Tableau (or similar BI tools) to support stakeholder reporting needs
• Collaborate with analytics engineering teams to improve data quality, pipelines, and reporting processes.

Experimentation & Insights

• Assist in executing the test roadmap aligned with marketing goals.
• Apply basic statistical methods to evaluate experiments and measure performance impact.
• Support the translation of findings into clear insights and actionable recommendations.
• Support MMM modeling efforts within Marketing Science by contributing to data inputs and assisting in the interpretation of model outputs for marketing measurement

Cross-Functional Collaboration

• Work closely with PMUA, GTM, Analytics, and Data Engineering teams to align on KPIs and measurement standards.
• Maintain documentation and support alignment across teams.
• Contribute to bi-weekly insights decks and leadership reporting.

About You

• 2+ years of experience in marketing analytics, data analytics, or a related quantitative field.
• 2+ years of experience writing complex SQL queries and working with large datasets.
• Experience with marketing attribution, paid media analytics, and performance measurement.
• Familiarity with marketing tools such as Google Analytics, Braze,Singular, Mixpanel  or similar platforms.
• Strong understanding of:
• Descriptive statistics
• Experimental design and A/B testing
• Key marketing KPIs (CAC, LTV, ROAS, retention)
• Familiarity with statistical methods and exposure to data science techniques (e.g., regression, experimentation, MMM) in a marketing analytics context.
• Experience with BI tools such as Tableau, Power BI, or similar.
• Strong communication skills with the ability to translate complex data into clear, actionable insights.
• Proven ability to collaborate across cross-functional and global teams.
• Bachelor’s degree in Statistics, Computer Science, Engineering, or a related quantitative field.

Good to Have

• Experience with cloud data warehouses such as Snowflake or Redshift.
• Exposure to Marketing Mix Modeling (MMM) or advanced attribution modeling.
• Experience with analytics engineering tools such as Databricks.
• Exposure to automation of marketing reporting pipelines.

A Day in the Life

• Analyze campaign performance across paid social, search, display, and offline channels.
• Evaluate incrementality tests and provide recommendations on budget allocation.
• Build dashboards and automated reports to scale insights delivery.
• Partner with marketing leads to refine KPIs and measurement frameworks.
• Deliver insights to leadership through structured storytelling and data visualization.
• Contribute to sprint planning and collaborate with global stakeholders to drive high-impact analytics initiatives.