Senior Data Engineer / ETL Developer

Responsibilities

• Build and maintain scalable batch and near real-time data pipelines
• Develop ETL solutions using Ab Initio, Python, PySpark, SQL and PL/SQL
• Review technical designs and convert solution blueprints into reusable code
• Integrate, cleanse, normalize, and transform data from multiple mortgage-related systems
• Partner with Product Owners, Architects, Engineers, and business stakeholders
• Support migration and modernization initiatives from legacy platforms to Google Cloud
• Build, schedule, orchestrate, and deploy solutions through enterprise CI/CD pipelines
• Support monitoring, operational excellence, root cause analysis, and production reliability

Required Qualifications

• 4+ years of Data Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
• 4+ years PL/SQL and SQL skills with proven experience in Oracle, Teradata, Python and/or BigQuery: complex query development, tuning, and debugging.
• 4+ years Ab Initio skills with proven experience to build complex graphs, Psets, performance tuning.
• 3+ years programming skills in Python; hands-on PySpark for distributed data processing
• 3+ years of ETL/ETL design, data warehousing concepts, and data modeling best practices

Desired Qualifications

• Financial Services or Mortgage industry experience
• Production operations experience: monitoring, SLAs, incident response, root cause analysis, and performance optimization.
• Experience working in hybrid environments (on-prem + cloud) and supporting data migration/modernization initiatives.
• Experience with scheduling/orchestration in Autosys and Airflow-based orchestration (Cloud Composer direction).
• Experience with Git-based workflows, code reviews, and automated testing practices for data pipelines.
• Experience with Harness, Jenkins and uDeploy based CICD environments.
• Practical experience using AI-assisted coding tools in daily development to improve productivity without compromising quality or security.
• Ab Initio development/maintenance experience and/or hands-on migration of Ab Initio graphs to modern Spark/SQL patterns.
• Experience with Dataplex and broader data governance concepts (metadata, classification, stewardship, lineage practices).
• Experience with Informatica Data Quality implementation patterns (profiling, rules, scorecards/metrics, exception workflows).
• Experience designing near real-time patterns (micro-batch/event-driven concepts) and handling late-arriving/out-of-order data.
• Familiarity with GCP operational practices for data workloads (service accounts/IAM basics, job monitoring, quota/cost controls).

Skills

• python
• data
• sql
• skills
• concepts
• bigquery
• etl
• pipelines
• cloud
• teradata sql
• ab initio