Job Title: Senior Data Engineer

Experience: 7+ Years
Employment Type: Full-time

Job Summary:

We are seeking a skilled Senior Data Engineer with strong experience in building scalable data pipelines and transforming complex data across enterprise platforms. The ideal candidate should have hands-on expertise in Databricks, PySpark, SQL, and ETL/ELT tools such as Informatica, AWS Glue, or DataProc. Experience with cloud data warehouses like Snowflake, BigQuery, or Delta Lake, and a strong understanding of data security, compliance, and DevOps is essential. Domain knowledge in banking, financial services, or cybersecurity is highly desirable.

Key Responsibilities:

Design, build, and optimize secure data pipelines for large-scale data processing.

Develop ETL/ELT jobs and implement Data Quality (DQ) rules within Databricks and Aurora platforms.

Collaborate with Data Architects, DQ Analysts, and Cyber SMEs in Agile POD teams.

Manage data modeling, performance tuning, and infrastructure cost optimization.

Support data governance, DQ controls (e.g., BCBS 239, DUSE, DMOVE), and compliance reporting.

Document architecture, test strategies, and ensure code quality and scalability.

Required Skills:

Strong proficiency in Databricks, PySpark, SQL

Experience with ETL tools (e.g., Glue, DataProc, ADF, Informatica)

Cloud experience with AWS, Azure, or GCP

Hands-on with data modeling, DQ implementation, and performance tuning

Understanding of data security, encryption, and risk controls

Excellent communication and stakeholder collaboration skills

Preferred Qualifications:

Bachelor’s degree in Computer Science, Engineering, or a related field

Experience in banking, financial services, or cybersecurity domains

Familiarity with DUSE/DMOVE frameworks and cybersecurity metrics reporting

Certification in cloud or data engineering tools is a plus