Technical Lead -Data Engineer

We are seeking a highly skilled and visionary Data Engineer Technical Lead to join our growing data engineering team. This role is ideal for someone who thrives on architecting scalable data solutions, leading high-impact projects, and mentoring a team of talented engineers. You will be instrumental in designing and implementing robust data architectures and ETL pipelines across Azure and AWS platforms to support our analytics, machine learning, and business intelligence initiatives.

Key Responsibilities:

• Lead Data Architecture Design: Define and implement scalable, secure, and high-performance data architectures across cloud platforms (Azure and AWS).
• Build & Optimize ETL Pipelines: Design, develop, and maintain robust ETL/ELT workflows for structured and unstructured data using tools like Azure Data Factory, AWS Glue, Apache Spark, and Databricks.
• Data Modeling: Create logical and physical data models that support business intelligence, analytics, and operational reporting.
• Cloud Data Engineering: Leverage cloud-native services (e. g. , Azure Synapse, AWS Redshift, S3, Lambda, EMR) to build modern data platforms.
• Technical Leadership: Mentor junior engineers, conduct code reviews, and enforce best practices in data engineering and DevOps.
• Performance Tuning: Optimize data storage, retrieval, and processing for performance and cost-efficiency.
• Data Governance & Security: Implement data quality, lineage, and security standards in compliance with organizational and regulatory requirements.
• Cross-Functional Collaboration: Work closely with data scientists, analysts, product managers, and business stakeholders to translate data needs into technical solutions.
• Bachelor s or Master s degree in Computer Science, Engineering, or a related field.
• 8+ years of experience in data engineering with at least 2 years in a technical leadership role.
• Proven expertise in data modeling (3NF, dimensional, data vault) and data architecture.
• Strong hands-on experience with Azure (Data Factory, Synapse, ADLS) and AWS (Glue, Redshift, S3, Lambda).
• Proficiency in SQL, Python, and Spark.
• Experience with CI/CD, infrastructure as code (Terraform, CloudFormation), and data orchestration tools (Airflow, Prefect).
• Familiarity with data governance, cataloging, and lineage tools (e. g. , Purview, Collibra, Alation).