Data Engineer ID94415
AgileEngine Gurgaon, Haryana, India
Software Development · 1,001-5,000 employees
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About the role
You will be responsible for executing large-scale data platform migrations to Snowflake and adapting existing pipelines to the new architecture. Additionally, you will support workflow scheduling and monitoring in Apache Airflow while ensuring data quality throughout the migration process.
What they look for
Requirements
The role requires 3+ years of Python development experience and advanced SQL skills including performance tuning. Candidates must also have hands-on experience with Snowflake data modeling, Apache Airflow, Spark/PySpark, and AWS S3.
Benefits
Full description
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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