Lead Data Engineer

Experienced Lead Data Engineering with a strong background in Big Data technologies, Scala, and Workday HCM integrations., * Lead end-to-end delivery of data engineering projects, ensuring timely and quality outcomes.

• Design, develop, and maintain scalable data pipelines using Databricks, Apache Spark (Scala), and AWS.
• Manage and coordinate with cross-functional teams including data analysts, data scientists, and business stakeholders.
• Drive data integration initiatives, including Workday HCM data extraction, transformation, and integration with downstream systems.
• Oversee ETL development and migration, especially from tools like Informatica PowerCenter to modern data platforms.
• Ensure data quality, validation, governance, and security across pipelines and storage systems.
• Optimize data processing workflows for performance, scalability, and cost efficiency.
• Translate business requirements into technical design and implementation plans.
• Provide technical leadership and mentorship to engineering teams.
• Manage project timelines, risks, dependencies, and stakeholder communication.

• 12+ years of IT experience with at least 5+ years in Big Data/Data Engineering.
• Strong expertise in Scala programming and Apache Spark (RDD, DataFrames, Spark SQL).
• Hands-on experience with Databricks and AWS ecosystem.
• Experience with Workday HCM integrations, including data extraction and transformation.
• Proficiency in SQL and data modeling concepts.
• Experience in ETL tools, especially Informatica PowerCenter, and migration strategies.
• Strong understanding of data pipeline architecture and distributed systems.
• Proven experience in project management and team leadership.
• Excellent communication and stakeholder management skills.

Preferred Qualifications

• Experience in Agile/Scrum methodologies.
• Exposure to data governance and compliance frameworks., Certification in AWS / Databricks / Project Management (PMP, Scrum Master) is a plus