Senior Assistant Vice President

Position Summary:

We are seeking a highly experienced and visionary Principal Data Engineer with over 20 years of industry experience to lead the design, development, and optimization of our enterprise-scale data infrastructure. This role is ideal for a seasoned data professional who thrives at the intersection of technology strategy, architecture, and hands-on engineering. You will drive innovation, mentor engineering teams, and collaborate with cross-functional stakeholders to enable data-driven decision-making across the organization.

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.