Job Title: Lead Data Engineer (Data Architecture Focus)
Experience: 7+ years
Role Overview
We are looking for a Lead Data Engineer who will own and drive data architecture decisions while leading data engineering initiatives. This role requires hands-on engineering expertise combined with architectural thinking, design authority, and technical leadership.
The ideal candidate will act as a Data Architect in practice, while being accountable for implementation, scalability, and long-term data platform strategy.
Key Responsibilities
- Own the end-to-end data architecture for enterprise-scale platforms, including data warehouses, data lakes, and lakehouse architectures.
- Design and define architectural standards, data models (conceptual, logical, physical), and integration patterns.
- Lead and mentor data engineers, ensuring best practices in pipeline design, coding standards, and performance optimization.
- Architect, build, and maintain robust ETL/ELT pipelines, batch and real-time data workflows.
- Drive technology selection and architectural decisions across cloud data platforms and analytics stacks.
- Ensure data governance, security, privacy, and compliance are embedded into the architecture and pipelines.
- Collaborate closely with business stakeholders, product teams, and analytics teams to translate requirements into scalable data solutions.
- Optimize data platforms for performance, reliability, scalability, and cost efficiency.
- Review and improve existing data architectures to eliminate technical debt.
- Act as the technical owner for data platform evolution and roadmap.
Required Skills & Expertise
- Strong hands-on experience in data engineering AND data architecture.
- Deep expertise in data modeling, schema design, and database architecture.
- Advanced proficiency in SQL and at least one programming language such as Python, Spark, or Scala.
- Hands-on experience with cloud platforms (AWS / Azure / GCP) and their native data services.
- Strong experience with modern data warehousing and lakehouse technologies (Snowflake, Databricks, Synapse, MS Fabric, etc.).
- Solid understanding of ETL/ELT frameworks, workflow orchestration, and data integration patterns.
- Knowledge of big data ecosystems (Kafka, Hadoop, Hive) is a strong plus.
- Strong grasp of data governance, metadata management, access control, and security best practices.
- Proven ability to lead technically, review designs, and influence architecture decisions.
- Excellent problem-solving, communication, and stakeholder management skills.
Preferred Qualifications
- Experience designing enterprise-grade data platforms at scale.
- Certifications in cloud platforms or data engineering technologies.
- Exposure to real-time / streaming data architectures.
- Familiarity with BI and analytics tools (Power BI, Tableau, Looker).