This is a remote position.

Screening Checklist:

Proficiency in interpreting data transformation logic written in T-SQL and implementing equivalent processes within Databricks

Ability to design and implement data ingestion pipelines using Azure Data Factory (from source to RAW layer)

Basic knowledge of C# and Sql(atleast read the coding, no need to write)

Experience in collecting and analyzing performance metrics to optimize data ingestion pipelines

Competence in performing performance optimizations for Databricks read/write queries as needed

Strong motivation and the ability to provide guidance to other data engineers within the team

Job Overview

We are currently looking for highly accomplished Senior Data Engineers (10+ years of experience)

with deep expertise in Databricks and PySpark to play a key role in an ongoing, large-scale data transformation initiative. The ideal candidates will bring extensive hands-on experience, strong architectural understanding, and the ability to lead and influence data engineering practices across teams.

Key capabilities and expectations include:

- Extensive experience in analyzing, interpreting, and modernizing complex data transformation logic written in T-SQL, and implementing optimized, scalable equivalents within

Databricks using PySpark.





- Proven expertise in architecting and implementing end-to-end data ingestion frameworks using Azure Data Factory, managing data flows from multiple source systems through the RAW and subsequent data layers, with a strong focus on reliability and scalability.
- Strong experience in defining, capturing, and analyzing performance metrics, enabling proactive monitoring, bottleneck identification, and continuous optimization of data ingestion pipelines.
- Demonstrated ability to perform advanced performance tuning and optimization of Databricks read/write operations, including partitioning strategies, caching, file formats, and query optimization techniques.
- Capability to provide technical leadership and mentorship to data engineering teams, establish best practices, conduct design reviews, and drive engineering excellence.
- Robust problem-solving skills, a results-oriented mindset, and the ability to collaborate effectively with cross-functional teams, including architects, analysts, and stakeholders.

This role demands a senior engineering mindset with a balance of deep technical expertise,

architectural ownership, and people leadership to deliver scalable, high-performance data solutions in an enterprise environment.

Educational qualifications:

Bachelors’s degree or Computer CIENCE

📌 Lead Data Engineer (India)
🏢 Awign Expert
📍 India