Data Lead / Data Architect

Job Descripon Senior Data Lead Posion Senior Data Lead Loca¢on [Insert Loca¢on / Remote / Hybrid] About the Role We are looking for a Senior Data Lead to work closely with our Data Architect and play a key role in execu¢ng the data strategy, building pipelines, and leading delivery of cri¢cal data projects. This is a hands-on technical leadership role youll design, code, review, and mentor engineers, while ensuring the data pla¢orm is reliable, governed, and future-ready. You will be the bridge between architecture and engineering execu¢on, transla¢ng architectural blueprints into scalable, produc¢on-grade solu¢ons. Key Responsibili¢es Pla¢orm & Pipeline Development ¢ ¢ ¢ ¢ Design and build scalable ETL/ELT pipelines for batch, near real-¢me, and streaming data. Implement data orchestra¢on workows (Airow, Dagster, Prefect, ADF). Op¢mize distributed data processing (Spark, Databricks, Flink, Ka¢a). Ensure data sharding, par¢¢oning, and performance op¢miza¢on in large-scale environments. ¢ Deploy and maintain data APIs, integra¢on services, and microservices. Governance & Quality ¢ ¢ ¢ Implement and enforce data quality checks, valida¢on rules, and observability frameworks. Maintain metadata, lineage, and documenta¢on to support governance. Partner with the architect to implement security, access control, and compliance requirements. Analy¢cs & AI/ML Enablement ¢ ¢ ¢ Enable BI/analy¢cs teams by building trusted datasets, marts, and seman¢c layers. Support data scien¢sts in deploying and opera¢onalizing predic¢ve models. Contribute to feature engineering pipelines and ML workows. Leadership & Delivery Lead a team of data engineers/analysts, providing technical mentorship and code reviews. ¢

¢ ¢ ¢ Ensure projects are delivered on ¢me, with high quality, and aligned to architectural guidelines. Collaborate with product, engineering, and business stakeholders to translate requirements into solu¢ons. Champion Agile/DataOps/MLOps prac¢ces across the data team. Required Skills & Experience ¢ ¢ 812 years in data engineering, with at least 3+ years in a lead/technical lead role. Strong exper¢se in Python/Scala/Java, SQL, and distributed compu¢ng (Spark, Databricks, Flink, Ka¢a). ¢ Proven experience with cloud data pla¢orms (AWS, Azure, GCP) and warehouses (Snowake, BigQuery, Redshi¢, Synapse). ¢ ¢ Hands-on with orchestra¢on tools (Airow, ADF, Prefect, Dagster). Experience with CI/CD pipelines, containers (Docker/Kubernetes), IaC (Terraform, CloudForma¢on). ¢ ¢ Solid knowledge of data governance prac¢ces, data catalogs, and observability. Strong problem-solving and debugging skills; able to op¢mize pipelines for performance and cost. ¢ Excellent communica¢on skills and ability to mentor junior engineers. Preferred Qualica¢ons ¢ ¢ ¢ ¢ Exposure to predic¢ve modelling, ML pipelines, and MLOps. Experience with streaming/real-¢me architectures (Ka¢a, Kinesis, Pub/Sub). Familiarity with data governance tools (Collibra, Ala¢on, Purview). Cer¢¢ca¢ons in cloud data engineering (AWS, Azure, GCP). What We Oer ¢ Opportunity to work side-by-side with the Data Architect to shape the companys data pla¢orm. ¢ ¢ ¢ A highly technical, hands-on role with freedom to innovate. Growth path into Architect/Head of Data Engineering roles. Work with modern data stack, cu¢ng-edge tools, and challenging big-data problems.