itD is seeking a Data Engineer to support a high-impact enterprise data migration initiative focused on transitioning business-critical operations from Salesforce to an internal entity-modeled data platform. This role will contribute directly to the success of Meta’s Developer Ecosystem Success organization by building scalable ETL pipelines and ensuring reliable, AI-ready data infrastructure across distributed systems.
Responsibilities:
- Design and build bidirectional ETL/ELT data pipelines between Salesforce, distributed data warehouses, and internal operational data platforms
- Develop and maintain streaming data pipelines using Kafka, Kinesis, Pulsar, or equivalent distributed event-streaming systems
- Design and manage dimensional and entity-modeled schemas, including access permissions and mutation rules
- Build data validation, reconciliation, and monitoring frameworks to ensure data quality, consistency, and auditability throughout migration activities
- Develop and maintain schema documentation, transformation logic, data dictionaries, and source-to-target mapping documentation
- Collaborate with software engineers, Salesforce administrators, and business stakeholders to define data contracts, SLAs, and migration requirements
- Investigate and resolve data quality issues, pipeline failures, and reconciliation discrepancies across batch and streaming workloads
- Utilize AI-assisted development tools such as GitHub Copilot, Cursor, and Claude Code to accelerate development workflows and schema migrations
- Support data restructuring and transformation initiatives to prepare datasets for downstream AI and analytics applications
- Attend regular internal practice community meetings
- Collaborate with your itD practice team on industry thought leadership
- Complete client case studies and learning material (blogs, media material)
- Build out material to contribute to the Digital Transformation practice
- Attend internal itD networking events (in person and virtual)
- Work with leadership on career fast-track opportunities
Requirements:
- 5+ years of professional data engineering experience
- Strong proficiency in SQL and relational databases such as MySQL
- Experience with Hack/PHP development and GraphQL
- Hands-on experience building and maintaining large-scale ETL/ELT pipelines in distributed data warehouse environments such as Hive, Spark, Presto/Trino, BigQuery, Snowflake, or Databricks
- Experience with real-time event-streaming systems including Kafka, Pulsar, Kinesis, or equivalent technologies
- Experience with ORM frameworks and entity/schema modeling
- Strong understanding of data quality engineering, validation, reconciliation, and monitoring frameworks
- Experience using AI-assisted coding tools such as GitHub Copilot, Claude Code, or Cursor within development workflows
- Strong troubleshooting, problem-solving, and communication skills with the ability to work independently
- Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related field required
- Experience with Salesforce data migrations and integrations
- Familiarity with AI-ready data architecture and AI development workflows
- Experience supporting event and subscription handling systems
- Prior experience working within large-scale technology or distributed systems environments
- Experience collaborating with cross-functional engineering and business operations teams