Execute large-scale data platform migrations to Snowflake, adapting approximately 1,000 datasets and existing pipelines. Develop, test, schedule, and monitor Airflow workflows while supporting migrations to Airflow 3, Iceberg, and new Confluent regions. Ensure data quality, reliability, performance, and timely completion of modernization initiatives through hands-on Python, SQL, Spark, Snowflake, Kafka, and AWS S3 engineering.
We are looking for a Data Engineer to execute large-scale data platform migrations to Snowflake and support reliable Airflow workflows.
The mandatory requirements are 3+ years of Python, advanced SQL, Snowflake data modeling, and hands-on experience with Airflow, Spark/PySpark, and AWS S3.
RECRUITMENT PROCESS
1. Application — Share a few details about your experience and background.
2. Coding Challenge — If applicable, complete it in the coding language you are most comfortable with.
3. Video Interview — Record a short video introduction in English.
4. Technical Interview or Hiring Manager Interview — Discuss your experience and fit for the role.
5. Offer — If it’s a match, you’ll receive an offer.
WHAT YOU’LL GAIN
• Remote work — Work from where you feel most productive.
• Local presence in India — Work in a structured and compliant environment aligned with Indian regulations.
• Competitive compensation in INR — Receive compensation in INR, plus support for learning, education, and wellness.
• Exciting projects — Work with modern technologies for global clients and fast-growing companies.
MUST HAVES
• Strong software engineering fundamentals.
• 3+ years of hands-on Python development experience.
• Advanced SQL, including complex joins, CTEs, window functions, and performance tuning.
• Snowflake data modeling.
• Apache Airflow — developing and testing pipelines in Airflow and Python.
• Apache Kafka.
• Apache Spark, including hands-on PySpark experience.
• Iceberg and Parquet data formats.
• AWS experience, particularly S3 (data lakes, partitioning, and lifecycle policies).
• Testing strategy experience, with the ability to hands-on debug and test code.
• At least 2 years of industry experience working with large-scale datasets, including Airflow and Spark.
• Overlap until 12 PM Pacific Time.
• Upper-intermediate English level.
NICE TO HAVES
• Hands-on experience with Snowflake migrations (data warehouse modernization, performance and cost optimization).
• Experience with Apache Airflow migrations (version upgrades, executor changes, or platform migrations).
• Experience using AI tools for development.
WHAT YOU WILL DO
• Work embedded within the data engineering function, partnering closely with the data platform team to support a large-scale data platform modernization effort.
• Execute the migration of approximately 1,000 datasets to Snowflake.
• Adapt existing pipelines to Snowflake, following the core architecture and technical approach defined by the internal team.
• Ensure data quality and reliability throughout the migration process.
• Support workflow scheduling and monitoring in Apache Airflow 3.
• Execute time-sensitive migrations, including Airflow 2 to 3, Confluent region migration, and the move to Iceberg.
• Help accelerate the migration initiatives targeted for completion by the end of March 2027.
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Execute large-scale data platform migrations to Snowflake, adapting approximately 1,000 datasets and existing pipelines. Build, test, monitor, and troubleshoot reliable Airflow workflows while supporting migrations from Airflow 2 to 3, Confluent regions, and Iceberg. Ensure data quality, performance, and reliability across large-scale datasets using Python, SQL, Spark, Kafka, AWS S3, and modern data formats. Collaborate with data platform teams on modernization initiatives through March 2027.
Top Skills:
Apache AirflowApache IcebergApache KafkaSparkAws S3ParquetPysparkPythonSnowflakeSQL
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