Technical Lead (Data Engineering)

Responsibilities:

• Drive the architectural vision for scalable, cost-optimized, and performant data systems
• Design, review, and guide the implementation of complex pipelines and data products
• Introduce and champion engineering best practices, design patterns, and quality standards
• Act as a force multiplier by mentoring engineers and helping them level up
• Represent the team in technical forums and work closely with leadership on strategic initiatives
• Bring a product mindset to engineering and advocate for the why as much as the how
• Keep your hands dirty: build things, break things (responsibly), and help your team learn from both
• Data Engineering Team members along with Principal engineers and Data Architects
• Product Managers and Product Leads across global business units
• Engineering managers and cross-team leads (DevOps, data science, and Analytics)
• Internal data consumers like Analysts, Business Intelligence, and ML teams
• Platform teams responsible for cost optimization and infrastructure scalability

Requirements:

• 6+ years of experience in data engineering, with 2+ years in a technical or team leadership role.
• Strong expertise in data architecture, data modelling, distributed computing, and modern data platforms.
• Proficiency with big data ecosystems like Spark, Databricks, Kafka, Presto, and Delta Lake.
• Strong coding skills in Python, Scala or Java, and a solid understanding of software engineering principles.
• Expertise in SQL/NoSQL, data and delta lakes, and cloud-native services (preferably AWS or GCP).
• Proven track record in building production-grade ETL pipelines and event-driven systems.
• Experience leading POCs, evaluating tools, and setting engineering best practices across teams.
• Familiarity with DataOps, DevOps and CI/CD, including tools for monitoring, alerting, and observability.
• A passion for mentoring and developing engineers and a love for collaborative problem-solving.