Senior Data Engineer / ETL Developer

Staffing Spot, Inc.; Charlotte (NC); Hybrid; USD 110,000 - 150,000; Full time

Job summary

Staffing Spot, Inc. is hiring a data engineer to build scalable batch and real-time data pipelines, using Ab Initio, Python, PySpark, SQL and PL/SQL. You will review designs and transform blueprints into reusable code, and transform mortgage data from multiple systems.

You will collaborate with product owners, architects, engineers and stakeholders; support migration to Google Cloud; and drive CI/CD and production reliability in a hybrid data environment.

Qualifications

• 4+ years of Data Engineering experience supporting data pipelines.
• 4+ years PL/SQL and SQL with Oracle, Teradata or BigQuery; complex queries.
• 4+ years Ab Initio to build graphs, Psets and performance tuning.
• 3+ years Python and PySpark for distributed data processing.

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 designs and translate blueprints into reusable code.
• Integrate, cleanse, normalize, and transform data from mortgage systems.
• Partner with Product Owners, Architects, Engineers, and stakeholders.
• Support migration and modernization to Google Cloud.
• Build, schedule, orchestrate, and deploy solutions via CI/CD.
• Support monitoring, incident response, and production reliability.

Skills

Python

PySpark

SQL

PL/SQL

Ab Initio

BigQuery

ETL

Data Warehousing

Data Modeling

GCP

Airflow

Autosys

CI/CD

Git

Dataplex

Informatica Data Quality

Tools

Autosys

Airflow

Git

Jenkins

uDeploy

Cloud Composer

Job description

Key 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 practicesDesired 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