AVP, Tech Lead, RDL

Key Responsibilities

• Design, implement, and maintain scalable data lake and lakehouse architectures using cloud-native services (AWS S3, Glue, Lake Formation, Delta Lake, Snowflake, etc.)
• Develop and optimize end-to-end data pipelines (batch and streaming) for ingesting, transforming, and storing structured and unstructured data at scale
• Integrate diverse data sources and ensure efficient, secure, and reliable data ingestion and processing
• Implement and enforce data governance, cataloging, lineage, and access controls (e.g., AWS DataZone / Glue Data Catalog or Unity Catalog, Collibra, Atlan)
• Collaborate with cross-functional teams (data scientists, BI engineers, product managers) to translate business needs into reliable, observable, and governed data products
• Drive adoption of modern data engineering frameworks (dbt, Airflow, Delta Live Tables, etc.) and DevOps practices (IaC, CI/CD, automated testing, monitoring)
• Champion data quality, security, and compliance (encryption, PII, GDPR, HIPAA, etc.) across all data lake/lakehouse operations
• Mentor and guide team members, contribute to platform roadmaps, and promote best practices in data engineering and Lakehouse design
• Stay current with emerging trends in data Lakehouse technologies, open-source tools, and cloud platforms

Qualification & Requirements

We’re looking for strong collaborators who deliver exceptional client experiences and thrive in fast-paced, team-oriented environments. Our ideal candidates pursue greatness, act with integrity, and are driven to help our clients succeed. We value those who embrace creativity, continuous improvement, and contribute to a culture where we win together and create and share joy in our work.

Required

• Proven track record of leading and developing high performing teams
• 10+ years of experience in data engineering, software engineering, and/or cloud engineering, with at least 5 years focused on leading and establishing data lake or lakehouse transformation via AWS
• Bachelor’s degree in Data Science, Computer science or related field; Master’s degree preferred
• Demonstrable hands-on experience with:
  • Cloud data lake architectures: AWS S3, Glue, Lake Formation, Snowflake, or similar
  • Data lake design patterns: raw, curated, consumption zones; medallion architecture
  • Data versioning and schema evolution: e.g., Delta Lake, Apache Iceberg
  • Data governance and cataloging: including any of the following (preferred experience in multiple tools) Unity Catalog, Collibra, Atlan, AWS Glue Data Catalog
  • Programming: Python and/or SQL (production code, reusable libraries, tests)
  • Pipeline orchestration: Airflow, Step Functions, dbt, or similar
  • DevOps for data: Terraform/CloudFormation, CI/CD, monitoring, and runbook creation
• Strong understanding of data modeling, data quality, and secure data onboarding/governance
• Experience with both batch and real-time data processing

Core Competencies

• Excellent communication and stakeholder management skills.

Preferred

• Experience with Spark, Snowflake or other big data frameworks
• AWS and/or Snowflake architect or developer certifications
• Demonstrated use of AI/ML tools to augment engineering productivity (prompting for code generation, LLMs for docs/tests, query optimization)
• Experience with knowledge graphs and semantic data modeling

Skills & Tools

• AWS (S3, Glue, Lake Formation, IAM), Snowflake
• SQL, Python
• dbt, Airflow, Step Functions
• Terraform/CloudFormation, CI/CD (GitHub Actions, Jenkins)
• Observability (Dynatrace preferred, Datadog, Prometheus)
• Data governance & security (Unity Catalog, Collibra, Atlan)
• LLM/AI augmentation tooling (preferred)

Benefits

No information available.