Data Infrastructure Engineer

What Will You Do?

• Design and implement resource-efficient, low-latency data pipelines.
  

• Explore, evaluate, and select suitable frameworks for data science and big data processing.
  

• Provide tools and best practices for data access control, data versioning, and migration strategies for other teams.
  

• Write clean, maintainable, and well-commented source code.
  

• Proactively address problems with a research-thinking mindset and critically think about the pros and cons of different approaches.
  

• Independently read relevant literature and share your insights and knowledge with other stakeholders.
  

• Work in a cross-functional team that takes ownership of the full software lifecycle.
  

• Collaborate with other teams to make optimal software architecture design decisions.
  

You should apply if you have

• Bachelor's degree in Technology (B.Tech),
  

• 4-8 years of relevant experience in business intelligence/data engineering
  

• Expertise in writing SQL (clean, fast code is a must) and in data-warehousing concepts such as star schemas, slowly changing dimensions, ELT/ETL, and MPP databases
  

• Experience working with distributed analytics databases like Redshift, BigQuery, Snowflake.
  

• ⁠Experience with various data integration systems like Airbyte, Stitch, Meltano etc.
  

• Understanding of data orchestration tools like Airflow, Mage, Prefect etc.
  

• Experience with consumer data platforms like Segment, Rudderstack.
  

• Experience working with reverse ETL systems like Hightouch.
  

• Experience with CDC systems like Debezium.
  

• Experience with Clickhouse.
  

• Experience with data lake technologies like Hudi, Iceberg and SQL query engines like Presto, Trino.
  

• Experience with dbt.
  

• Understanding of various data modeling architectures like Kimball, Inmon, Data Vault.⁠⁠
  

• Knowledge of data catalog tools like Amundsen, LinkedIn Datahub or data observability tools like Monte Carlo.
  

• Understanding of CI/CD systems and implementation of good software engineering practises to enable safe development with large teams.