Data Engineer ID94415

AgileEngine, LLC.; Bengaluru Urban; Hybrid; INR 1,500,000 - 2,100,000; Full time

Benefits offered by this job

Remote work

India presence

Competitive INR compensation

Global clients

Job summary

AgileEngine, LLC in Bengaluru is seeking a Data Engineer to execute large-scale data migrations to Snowflake and maintain reliable Airflow workflows. You will migrate around 1,000 datasets, adapt pipelines to Snowflake, and ensure data quality across the platform.

The role demands strong Python, advanced SQL, Spark/PySpark, Iceberg/Parquet, and AWS S3 experience, plus a solid testing mindset. This role supports global clients with remote work options.

Qualifications

• 3+ years of hands-on Python development experience.
• Advanced SQL with complex joins, CTEs, window functions, and tuning.
• Experience with Apache Airflow for pipelines development and testing.
• PySpark experience and Spark-based data processing.
• Familiarity with Iceberg and Parquet formats on data lakes.
• AWS S3 data lake experience including partitioning and lifecycle policies.
• Testing strategy experience with hands-on debugging and validation.
• Minimum 2+ years in roles handling large-scale datasets with Airflow/Spark.
• Overlap until 12 PM Pacific Time for collaboration.

Responsibilities

• Support a large-scale data platform modernization within the data engineering function.
• Migrate approximately 1,000 datasets to Snowflake as part of the migration effort.
• Adapt existing pipelines to Snowflake following internal architecture guidance.
• Ensure data quality and reliability throughout the migration process.
• Support workflow scheduling and monitoring in Airflow.
• Execute time-sensitive migrations including Airflow upgrades and Iceberg transition.

Skills

Python development

Advanced SQL

Apache Airflow

Apache Spark / PySpark

Iceberg / Parquet

AWS S3

Testing strategy

Large-scale datasets

Overlap 12 PM PT

Software engineering fundamentals

Job description

Bangalore North, India | Posted on 10/08/2026

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.