Director / Associate Director – Data Engineering

Role Overview

Key Responsibilities

• Lead end-to-end data engineering strategy and solution delivery for multiple projects.
• Collaborate with enterprise clients to define data architectures, platform modernization strategies, and transformation roadmaps.
• Drive the design and implementation of cloud-native data pipelines, data lakes, and data warehouses.
• Manage project budgets, resourcing, timelines, and stakeholder communications.
• Build, lead, and mentor high-performing data engineering teams across cloud platforms.
• Define and enforce engineering standards, governance, and best practices.
• Ensure quality, scalability, and performance across all data solutions.
  

Required Skills & Qualifications

• 10–15 years in data engineering or data platform development, including at least 3+ years in director-level or senior leadership roles.
• Proven success in delivering large-scale, cloud-based data solutions.
• Strong people leadership, client management, and delivery ownership experience.
  

Data Engineering & Tools

• Strong experience building ETL/ELT pipelines using tools like Spark, PySpark, Python, SQL, Airflow, dbt, etc.
• Solid knowledge of data lake/lakehouse/warehouse architectures.
• Experience with batch and real-time streaming data processing.
• Strong data modeling (star/snowflake schema), data partitioning, and performance tuning.
  

Cloud & Platform Expertise

• Experience with any major cloud provider – AWS, Azure, or Google Cloud Platform (GCP).
• Deep understanding of cloud-native data architecture, including storage, compute, networking, and security considerations.
• Hands-on experience with services like:
• AWS: Redshift, Glue, S3, Lambda, EMR, Kinesis
• Azure: Data Lake, Synapse, ADF, Databricks, Event Hub
• GCP: BigQuery, Dataflow, Pub/Sub, Composer
  

Governance & Quality

• Knowledge of data cataloging, data quality, lineage, and governance frameworks.
• Familiarity with security and compliance requirements (e.g., GDPR, HIPAA) in data platforms.
  

Preferred Qualifications

• Certifications in cloud platforms (AWS, Azure, or GCP).
• Experience with CI/CD pipelines, DevOps for data, and infrastructure as code (Terraform/CloudFormation).
• Exposure to analytics and BI tools (Power BI, Tableau, Looker).
• Familiarity with data mesh, data fabric, or modern data architecture patterns.