DoorDash
About this role
DoorDash's Analytics Engineering team sits between analytics and data engineering, and builds the internal data products that let business teams across Product, Operations and Finance make decisions quickly and reliably. As an Analytics Engineer in Hyderabad you own the data foundations: you build and maintain high volume, reliable ETL and ELT pipelines using data lake and warehousing concepts, design the canonical datasets and metrics the company trusts, and build the self serve tools and dashboards (Tableau, Sigma, Mode) that let analytics scale without a human in the loop for every question. It is a genuinely technical role, strong SQL plus Python or Scala, embedded across several business domains. The stated bar is 5+ years. Good fit for an analytics or data engineer who cares about data integrity and reusability and likes being the person who turns messy business questions into trusted data.
Who this is for
What the posting asks for:
- 5+ years in business intelligence, analytics engineering, data engineering or a similar role.
- Strong SQL for data transformation, and comfort in at least one functional or object oriented language such as Python or Scala.
- Expertise building reporting and data visualisation with tools like Looker, Tableau or Sigma.
- Familiarity with database fundamentals (S3, Trino, Hive, Spark) and SQL performance tuning, plus experience writing data quality checks (Pydeequ, Great Expectations).
The day to day: you translate business needs into data requirements, build and maintain canonical datasets and high volume ETL and ELT pipelines, lead the development of self serve data products, design metrics and dashboards, and champion high data integrity, reusability and standardisation across domains.
Location: Hyderabad.
Honest read: a strong, technical data role that leans analytics engineering rather than pure platform work. If you enjoy modelling data and building the datasets and tools the whole company relies on, it is a good fit. The 5+ years and SQL depth are real.
- 5+ years in business intelligence, analytics engineering, data engineering or a similar role.
- Strong SQL for data transformation, and comfort in at least one functional or object oriented language such as Python or Scala.
- Expertise building reporting and data visualisation with tools like Looker, Tableau or Sigma.
- Familiarity with database fundamentals (S3, Trino, Hive, Spark) and SQL performance tuning, plus experience writing data quality checks (Pydeequ, Great Expectations).
The day to day: you translate business needs into data requirements, build and maintain canonical datasets and high volume ETL and ELT pipelines, lead the development of self serve data products, design metrics and dashboards, and champion high data integrity, reusability and standardisation across domains.
Location: Hyderabad.
Honest read: a strong, technical data role that leans analytics engineering rather than pure platform work. If you enjoy modelling data and building the datasets and tools the whole company relies on, it is a good fit. The 5+ years and SQL depth are real.
Apply on company site
Opens job-boards.greenhouse.io, the employer's own application page. Applying is always free.