Data Engineer ID94415

AgileEngine, LLC.; Hyderabad; Hybrid; INR 1,200,000 - 1,800,000; Full time

Benefits offered by this job

Remote work

Local presence in India

INR compensation

Learning support

Exciting projects

Job summary

AgileEngine, LLC. is seeking a Data Engineer to execute large-scale data platform migrations to Snowflake and support reliable Airflow workflows. You will work on modern technologies for global clients from a remote India environment with local presence.

The role offers competitive compensation in INR and opportunities for learning and wellness. The must-haves include 3+ years of Python, advanced SQL, Snowflake data modeling, and hands-on Airflow, Spark/PySpark, and AWS S3 experience, along with

Qualifications

• 3+ years of hands-on Python development.
• Advanced SQL with complex joins, CTEs, window functions, and tuning.
• Experience with Apache Airflow pipelines in Python.
• Hands-on Spark / PySpark for large-scale datasets.
• Snowflake data modeling or migrations experience.
• AWS S3 data lakes, partitioning, lifecycle policies.
• Testing strategy and debugging of data pipelines.
• 2+ years of industry experience with large-scale datasets and Airflow/Spark.
• Overlap until 12 PM Pacific Time.

Responsibilities

• Embed within data engineering to support modernization of the data platform.
• Migrate ~1,000 datasets to Snowflake.
• Adapt existing pipelines to Snowflake architecture following internal standards.
• Ensure data quality and reliability during migration.
• Support workflow scheduling and monitoring in Apache Airflow.
• Execute migrations including Airflow 2 to 3 and Iceberg move.
• Help accelerate migration initiatives by end of March 2027.

Skills

Python development

Advanced SQL

Airflow

Spark / PySpark

Data platform migrations

Data quality testing

Tools

Snowflake

Apache Airflow

Apache Spark

Iceberg

Parquet

AWS S3

Confluent

Job 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.

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.
• Apache Airflow — developing and testing pipelines in Airflow and Python.
• 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.

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.