Data Engineer

Role- Data Engineer

Location:

Key Responsibilities

• Design, build, and optimize

  data pipelines

  using

  PySpark

  and

  Apache Airflow

  for large-scale ETL processes.
• Develop and maintain

  big data solutions

  in

  Python

  , ensuring scalability and efficiency.
• Write, optimize, and tune

  complex Oracle SQL / PL-SQL queries

  for data management and analytics.
• Implement and maintain

  data warehouse solutions

  (star/snowflake schema, facts/dimensions, SCDs).
• Translate

  banking domain use cases

  (e.g., NPA, provisioning, regulatory reporting) into scalable data pipelines.
• Monitor, troubleshoot, and optimize workflows, batch jobs, and data accuracy.
• Collaborate with business analysts and domain experts to deliver high-quality, reliable solutions.
• Maintain

  technical documentation, data dictionaries, and lineage reports

  for audits and compliance.
• Continuously explore and adopt new tools and technologies in the

  data engineering

  ecosystem.

Must-Have Skills

• Strong expertise in

  Oracle SQL / PL-SQL

  (query design, schema management, performance tuning).
• Hands-on experience with

  PySpark

  for big data processing.
• Proven experience with

  Apache Airflow

  for ETL and workflow orchestration.
• Strong

  Python programming

  skills for data engineering.
• Solid understanding of

  data warehouse concepts

  (star/snowflake schema, facts/dimensions, SCDs).
• Familiarity with

  banking/financial domain processes

  (NPA, provisioning, regulatory reporting).
• Strong problem-solving skills including debugging and performance optimization.
• Proficiency in

  Git/version control

  .
• Excellent communication and teamwork abilities with strong attention to detail.