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Senior Assistant Vice President
4 weeks ago
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.
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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.
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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.
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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.
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