Job Summary

We are looking for a sharp, execution-focused Data Engineer to join Salesforce's internal Data Platform team. In this role, you will architect and deliver mission-critical data pipelines that power Informatica's enterprise operations — from financial reporting to Salesforce writeback. You will own complex end-to-end data flows, drive performance at scale, and set the engineering bar for a high-impact team.

Key Responsibilities

Engineering & Delivery

• Design and build highly complex Informatica IICS mappings, taskflows, workflows, and API integrations from requirements through production.
• Write performance-tuned SQL against Azure SQL DB, snowflake, ADLS Gen 2, and other enterprise data stores to implement business-critical logic.
• Orchestrate pipelines via Unix shell scripts; implement scheduling with crontab or equivalent for non-standard intervals.
• Lead performance tuning initiatives — identify bottlenecks, reduce runtimes, and harden pipelines for production reliability.
• Conduct design reviews and code walkthroughs with senior technical audiences; incorporate feedback and maintain knowledge-base articles.

  Platform & Architecture

  • Scale a complex, multi-system data platform spanning cloud (SFDC, Oracle Cloud) and on-premise data sources.
  • Apply best practices in DWH architecture, data lake design, and ETL engineering to continuously raise the quality bar.
  • Uncover and champion better ways to build — introduce tooling, patterns, and automation that multiply team output.

Skill Requirements

Must-Have

• 5+ years hands-on ETL development with Informatica IICS and IDQ — including deep knowledge of internal architecture.
• Expert-level SQL skills across relational and cloud databases (Azure SQL DB, ADLS Gen 2, Snowflake, or equivalent).
• Strong Unix/Linux scripting; experience automating pipeline orchestration via shell and cron.
• Working knowledge of cloud platforms — Salesforce (SFDC), Oracle Cloud, or equivalent SaaS ecosystems.
• Exceptional debugging and triage skills; proven ability to diagnose and resolve production incidents under pressure.
• Strong analytical thinking with the ability to break down ambiguous problems into clear, executable solutions.

Other Requirements

Strongly Preferred

• 3–7 years delivering production ETL/ELT on data lakes, data warehouses, or analytical platforms.
• Experience with DBT, Snowflake, Jupyter Notebook, Databricks, and Postman for exploratory analysis and API testing.
• Familiarity with Python for data engineering, automation, or lightweight analytics.
• Track record of leading teams through re-platform or technology modernization efforts.
• Knowledge of agile project planning methodologies; experience working directly with Scrum teams.

Nice to Have

• Exposure to data science, machine learning, or advanced analytics tooling.
• Experience building or consuming REST APIs in data pipeline contexts.
• Informatica certifications or participation in Informatica community / partner programs.