PySpark Data Engineer – Assistant Vice President

Develop and maintain scalable, extensible, and highly available data solutions supporting regulatory and business decision requirements.

Collaborate closely with stakeholders to deliver data products aligning with architectural standards and business priorities in an agile environment.

Identify and mitigate risks in the data supply chain, and follow or contribute to technical standards and best practices.

9 to 11 years of experience implementing data-intensive solutions using agile methodologies.

First Class Degree in Engineering or Technology (4-year graduate course) mandatory.

Hands-on experience in building ETL data pipelines and proficiency in two or more data integration platforms such as Ab Initio, Apache Spark, Talend, or Informatica.

Strong knowledge of relational (e.g., Oracle, MSSQL, MySQL) and NoSQL databases (e.g., MongoDB, DynamoDB), cloud native technologies, and programming in Python, Java, or Scala.

Experienced in data warehousing, data modeling, and big data platforms like Hadoop, Hive, or Snowflake with ability to design and optimize data models for analytics consumers.

Skilled in automation and DevOps practices including CI/CD, version control, and automated quality control for data pipeline deployments.

Capable of mentoring others and independently owning medium-sized components, with strong communication and problem-solving skills in a regulated financial environment.