Senior Assistant Vice President

Position Summary

Principal Data Engineer

Key Responsibilities

• Architecture & Strategy
• Define and own the data engineering roadmap, architecture, and data platform strategy.
• Evaluate and implement scalable, secure, and cost-effective data technologies.
• Lead the transition to modern data platforms (e.g., cloud, data lakehouse, streaming architecture).
• Engineering Leadership
• Lead end-to-end design and development of robust ETL/ELT pipelines, data lakes, and real-time streaming systems.
• Provide hands-on guidance on data modeling, pipeline optimization, and system integration.
• Oversee deployment and automation of data pipelines using CI/CD, orchestration tools (e.g., Airflow), and infrastructure-as-code.
• Data Governance & Quality
• Define best practices for data governance, lineage, privacy, and security.
• Implement data quality frameworks and monitoring strategies.
• Cross-Functional Collaboration
• Work closely with data scientists, analysts, product owners, and engineering leaders to define data requirements.
• Serve as a thought leader and technical advisor to senior management and stakeholders.
• Mentorship & Team Development
• Mentor and coach senior engineers and technical leads.
• Lead architectural reviews, code reviews, and foster a culture of technical excellence.

Required Qualifications:

• 20+ years of hands-on experience in data engineering, software engineering, or data architecture.
• Proven track record of building and scaling enterprise data platforms and systems.
• Deep expertise in SQL, Python/Scala/Java, Spark, and distributed data systems.
• Strong experience with cloud platforms (AWS, GCP, or Azure), especially cloud-native data tools (e.g., Redshift, BigQuery, Snowflake, Databricks).
• Experience with real-time streaming technologies (Kafka, Flink, Kinesis).
• Solid understanding of data modeling (dimensional, normalized, NoSQL).
• Familiarity with DevOps and MLOps practices in a data environment.
• Excellent communication skills and ability to influence at the executive level.
  

Preferred Qualifications:

• Master’s or Ph.D. in Computer Science, Data Engineering, or a related field.
• Experience in regulated industries (e.g., finance, healthcare).
• Prior experience in global organizations and managing geographically distributed teams.