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).