Senior Data Engineer(Experience 10+ year )

About the Role:

Duration: 12 months

Location: Remote

Timings: Full Time (As per company timings)

Notice Period: (Immediate Joiner - Only)

Experience: 10-12 Years

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.

• Strong 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 Science