Data manager/senior data manager (Polanco)

About the Company

We are seeking a Senior Data Engineering Manager to lead a small, high-performing data engineering team delivering scalable, reliable, and cost-effective data staging and analytics solutions across the enterprise data ecosystem. This role owns the operational reliability, performance, and continuous improvement of data platforms that power business intelligence, reporting, and emerging advanced analytics use cases.

Responsibilities

• Lead, mentor, and develop a small team of data engineers (currently ~3 people, growing).
• Establish clear delivery processes (intake, estimation, backlog management, sprint planning, release coordination).
• Oversee operational support, incident management, and structured root cause analysis for data pipelines.
• Create a healthy team dynamic by coaching, supporting, and developing junior engineers.
• Own structured intake and estimation processes for new data initiatives.
• Provide transparent status reporting and maintain alignment with enterprise data strategy.
• Deliver curated datasets and staging solutions across Snowflake (centralised analytics and aggregation layers), Postgres, and cloud data services (Azure/AWS).
• Design and implement robust ETL/ELT pipelines for scalable, reliable ingestion and transformation.
• Implement version control, automated testing, and CI/CD practices for data pipelines.
• Optimise workload placement to balance cost, performance, scalability, and maintainability.
• Deliver structured, analytics‑ready data for BI/reporting consumers and enable future advanced analytics.
• Design pipelines that support semi‑structured data and reproducible patterns suitable for ML/AI needs as they arise (not an AI engineering role).
• Reduce avoidable Snowflake spend through better design.
• Implement data quality monitoring, observability, lineage, and measurable SLAs for critical datasets.
• Partner with Enterprise Data Architecture to align engineering deliverables with target‑state models, standards, and governance.

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent practical experience.
• ~8+ years' experience in data engineering, data warehousing, or analytics engineering with ownership of production‑grade data platforms.
• Strong SQL skills and hands‑on experience building and operating production data pipelines.
• Experience designing and operating modern ETL/ELT pipelines using tools such as Talend (or comparable platforms).
• Working experience with Snowflake or similar cloud data warehouse platforms.
• Experience with Postgres (or comparable relational databases) and sound judgement on workload placement decisions.
• Experience implementing data testing, monitoring, and observability practices.
• Comfortable using AI‑assisted engineering tools to improve productivity while maintaining security, quality, and governance.
• Hands‑on Talend experience (Talend Cloud and/or Remote Engine) in an enterprise environment.
• Experience working in hybrid cloud and on‑prem data ecosystems.
• Experience implementing metadata/lineage practices or data catalog tools.
• Experience supporting enterprise BI platforms such as Power BI.
• Exposure to data preparation patterns that support ML/predictive analytics initiatives.