Job Description Role Purpose: To ensure the organization has reliable, well-governed, and analytics-ready data by building and maintaining robust data pipelines and models. The role exists to make trusted data available securely and cost-effectively to support enterprise reporting, BI, and data-driven decision-making. Key Responsibilities: 1- Enterprise Data Ingestion and Data Engineering; * Build reusable, parameterized mappings and task flows in Informatica IDMC to standardize data ingestion. * Implement change data capture (CDC), idempotent loads, schema evolution, and data-quality gates. * Optimize Big Query loads using partitioning, clustering, and the appropriate load-versus-stream approach. * Set up version control and CI/CD pipelines for data engineering assets. 2- Data Mapping & Transformation Design; * Profile source systems and define field-level mappings and transformation rules. * Specify business logic, including joins, lookups, and derivations. * Define data-quality rules, exception handling, and reject criteria. 3- Orchestration, Automation & Reliability Engineering; * Parameterize task flows and configure schedules and dependencies. * Implement retries, backoff, and checkpointing to ensure reliable processing. * Integrate monitoring and alerting through the Ops console and ChatOps. 4- Data Roles and Privacy management; * Define least-privilege IAM roles and service accounts for data access. * Apply dataset, table, row, and column-level security and data masking. * Enable audit logging and retention policies, and classify PHI/PII data. 5- Modern Data Architecture & Data Modelling; * Implement Medallion Architecture across the Bronze, Silver, and Gold layers. * Develop scalable, curated data models for analytical and reporting needs. * Define data quality, lineage, and governance standards for curated data. * Collaborate with business and analytics teams to create trusted datasets. 6- Workload Monitoring, Performance & Cost Optimisation; * Track data freshness, job health, volumes, and anomalies. * Monitor SLAs across job duration, errors, cost per TB, and slot usage. * Tune BigQuery performance through query optimisation and resource management. * Optimize cost through storage lifecycle management, query tuning, and caching. Skills * Data Engineering Tools: Informatica IDMC, Airflow, Apache Spark. * Programming Languages: SQL, Python. * Cloud Technologies: Google Cloud Platform (BigQuery, IAM), Azure/AWS (optional). * Visualization & BI Platforms: Power BI, Looker, Looker Studio, Tableau. * Strong in BigQuery (SQL, modelling, tuning). * Proficient with Informatica IDMC/IICS ETL/ELT. * Experience with end-to-end enterprise data pipelines using GCP and Informatica IDMC. * Knowledge of Medallion Architecture. * Experience building reporting-ready data marts and BI datasets. * Experience supporting enterprise BI dashboards and self-service analytics is preferred. * Knowledge of healthcare data (claims, providers, members). * Understanding of cloud security (IAM, service accounts, private endpoints). Education Bachelor’s degree in Computer Science, Information Technology, Information Systems, or a related