Data Engineer - Informatica

Data Engineer - Informatica Location: Remote -EST working hours Length of Contract: 3-9 months Hourly Pay: 65.00 p/hr - W2 40 hours per week • No 3rd Party Vendors • • W2 Contract Only • PERFORMANCE DETAILS 1. What’s the major objective(s) of the role? • Building and optimizing ETL processes using Informatica PowerCenter to extract, transform, and load data from multiple sources into centralized data warehouses or cloud environments. • Ensuring data quality, consistency, and accuracy across systems by implementing validation, cleansing, and transformation logic. • Developing and optimizing SQL queries for efficient data retrieval, analysis, and reporting. • Leveraging cloud platforms (such as AWS, Azure, or GCP) to design scalable, secure, and cost-effective BI solutions. • Collaborating with business stakeholders to understand reporting and analytics needs, then translating them into technical solutions. • Enabling self-service analytics by delivering structured data models, dashboards, and reporting frameworks for end-users. 1. What are the MUST-HAVE technologies for this position? • ETL / Data Integration Tools • Informatica PowerCenter (core requirement for ETL design and data integration) • Informatica Cloud (for hybrid/cloud data integration, if applicable) • Databases and Query Languages • SQL (advanced proficiency for writing complex queries, stored procedures, and performance tuning) • Relational Databases such as Oracle, SQL Server, PostgreSQL, or MySQL • Exposure to Data Warehousing concepts (Star/Snowflake schema, fact/dimension modeling) • Cloud Platforms (at least one major provider) • Azure (Synapse Analytics, Data Factory, Blob Storage) • Data Modeling & Warehousing • Dimensional modeling • Data warehouse/lakehouse platforms (Snowflake, Databricks, or equivalent) 1. What are the MUST-HAVE Critical Skills for this position • Performance Optimization • Experience in tuning ETL jobs and optimizing SQL queries for large data volumes. • Ensuring data pipelines are efficient, reliable, and scalable. • Data Quality & Governance • Implementing data validation, cleansing, and transformation rules. • Understanding of data security, compliance, and governance best practices. • Problem-Solving & Analytical Thinking • Strong skills in analyzing business requirements and translating them into technical solutions. • Ability to troubleshoot complex ETL, SQL, and data pipeline issues. • Collaboration & Communication • Ability to work closely with business stakeholders to understand reporting needs. • Clear communication of technical concepts to non-technical users. • Adaptability & Continuous Learning • Keeping up with evolving cloud technologies and BI tools. • Flexibility to work across different databases, integration tools, and visualization platforms 1. What are the NICE TO HAVE technologies • Advanced Cloud Data Ecosystem • Azure: Data Factory, Databricks, Cosmos DB • Snowflake or Databricks for modern data warehousing and lakehouse solutions • BI & Visualization Tools • Power BI, Tableau, Qlik, or Looker for dashboarding and self-service analytics • Programming & Scripting Languages • Python or R for data manipulation, automation, and advanced analytics • Shell scripting for workflow automation and ETL orchestration • Data Governance & Quality Tools • Collibra, Alation, or Informatica Data Quality (IDQ) for metadata management and governance • Master Data Management (MDM) tools for enterprise data consistency