Data Engineer

About the Role We are seeking an experienced and driven Data Engineer with deep expertise in Informatica PowerCenter / IICS and Snowflake to join our growing data engineering team. You will be responsible for designing, building, and optimizing data pipelines, integration workflows, and cloud data solutions that power critical business insights across the organization. Key Responsibilities Data Integration & ETL Development • Design, develop, and maintain ETL/ELT pipelines using Informatica PowerCenter and Informatica Intelligent Cloud Services (IICS). • Build robust data ingestion workflows from on-premise and cloud-based source systems (ERP, CRM, flat files, APIs, databases). • Implement incremental and full-load strategies, CDC (Change Data Capture), and data replication patterns. • Debug, tune, and optimize existing Informatica mappings, sessions, and workflows for performance and reliability. Snowflake Data Warehousing • Architect and develop scalable data models in Snowflake including staging, dimensional, and analytics layers. • Write advanced SQL for complex transformations, stored procedures, dynamic tables, tasks, and streams in Snowflake. • Leverage Snowflake-native features: Time Travel, Data Sharing, Zero-Copy Cloning, Clustering, and Materialized Views. • Monitor and optimize query performance using Snowflake's Query Profile, result caching, and virtual warehouse sizing. • Manage Snowflake environments (Dev, UAT, Prod) including role-based access control (RBAC) and data security policies. Data Modeling & Architecture • Design conceptual, logical, and physical data models following Kimball, Inmon, or Data Vault methodologies. • Collaborate with data architects to define standards for schema design, naming conventions, and documentation. • Build and maintain metadata, data lineage, and cataloging assets using Informatica Axon or similar tools. Collaboration & Delivery • Work closely with business analysts, data scientists, and BI teams to understand requirements and deliver data products. • Participate in Agile sprints, technical design reviews, and data governance meetings. • Create and maintain technical documentation including data flow diagrams, mapping specifications, and runbooks. • Support production issues, perform root cause analysis, and implement fixes within agreed SLAs. Required Qualifications & Skills Core Technical Skills Informatica Snowflake • Informatica PowerCenter 9.x / 10.x • Informatica IICS (CDI, CAI, MDM) • Mapping Designer, Workflow Manager • Pushdown Optimization (PDO) • Informatica Data Quality (IDQ) • Snowflake SQL & SnowSQL CLI • Streams, Tasks & Dynamic Tables • Snowpipe & Data Loading (COPY INTO) • Virtual Warehouses & Resource Monitors • Secure Data Sharing & Marketplace Additional Technical Skills • Strong proficiency in SQL (complex joins, window functions, CTEs, performance tuning). • Experience with Python or Shell scripting for automation and data processing. • Familiarity with cloud platforms: AWS (S3, Glue, Lambda), Azure (ADF, ADLS), or GCP (BigQuery, Dataflow). • Knowledge of version control tools (Git/Bitbucket) and CI/CD pipelines for data workflows. • Exposure to orchestration tools such as Apache Airflow, Control-M, or Autosys. • Understanding of data governance concepts: data lineage, cataloging, and master data management. Education & Experience • Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field. • 3–8 years of hands-on experience in data engineering, ETL development, and data warehousing. • Minimum 2 years of dedicated experience with Informatica (PowerCenter or IICS). • Minimum 2 years of experience working on Snowflake in a production environment. Preferred Qualifications (Nice to Have) • Informatica Certified Data Engineer or Snowflake SnowPro Core / Advanced certification. • Experience with dbt (data build tool) for transformation layer on Snowflake. • Familiarity with streaming data platforms like Apache Kafka or AWS Kinesis. • Experience working in an Agile / Scrum delivery environment. • Exposure to BI tools such as Tableau, Power BI, or Looker for downstream consumption. • Knowledge of data mesh, data lakehouse architectures, or medallion (Bronze/Silver/Gold) design patterns.