Core Responsibilities:

- Lead end-to-end design, development, and delivery of complex cloud-based data pipelines.

- Collaborate with architects and stakeholders to translate business requirements into technical data solutions.

- Ensure scalability, reliability, and performance of data systems across environments.

- Provide mentorship and technical leadership to data engineering teams.

- Define and enforce best practices for data modeling, transformation, and governance.

- Optimize data ingestion and transformation frameworks for efficiency and cost management.

- Contribute to data architecture design and review sessions across projects.

Qualifications:

- Bachelor's or Master's degree in Computer Science, Engineering, or related field.

- 8+ years of experience in data engineering with proven leadership in designing cloud-native data systems.

- Strong expertise in Python, SQL, Apache Spark, and at least one cloud platform (Azure, AWS, or GCP).

- Experience with Big Data, Data Lake, DeltaLake, and Lakehouse architectures.

- Proficient in one or more database technologies (e.g. PostgreSQL, Redshift, Snowflake, and NoSQL databases).

- Ability to recommend and implement scalable data pipelines.

Preferred Qualifications:

- Cloud certification (AWS, Azure, or GCP).

- Experience with Databricks, Snowflake, or Terraform.

- Familiarity with data governance, lineage, and observability tools.

- Strong collaboration skills and ability to influence data-driven decisions across teams.