Job Specifications
Immediate need for a talented Data SDET Engineer. This is a 12+ months contract opportunity with long-term Potential and is located in Pittsburg, PA / Lake Marry, FL (Hybrid). Please review the job description below and contact me ASAP if you are interested.
Job Diva ID: 26-09773
Pay Range: $45 - $50/hour. Employee benefits include, but are not limited to, health insurance (medical, dental, vision), 401(k) plan, and paid sick leave (depending on work location)
Key Responsibilities;
Data Testing & Quality Engineering
Design and implement automated data validation frameworks for ETL and ELT pipelines
Validate data completeness, accuracy, consistency, timeliness, and integrity
Perform source-to-target reconciliation across large-scale datasets
Execute end-to-end data pipeline testing across ingestion, transformation, and consumption layers
Develop automated regression and smoke tests for data pipelines
ETL & Pipeline Validation
Test and validate ETL processes built using tools such as:
Apache Airflow
Spark / PySpark
SQL-based transformations
Cloud-native ETL solutions (AWS / Azure / GCP)
Log, analyze, and debug data issues in complex distributed systems
Ensure data pipelines meet performance and scalability standards
Python Automation & Framework Development
Write clean, modular, production-grade Python code
Build and enhance test automation frameworks using Python and PyTest
Develop reusable automation utilities for data profiling and validation
Integrate automation into CI/CD pipelines
Collaboration & Growth into Data Engineering
Work closely with Data Engineers to understand pipeline design and architecture
Assist in optimizing data pipelines and transformations
Contribute to data modeling, schema design, and pipeline improvements
Gradually transition toward implementing data transformations and engineering solutions
Key Requirements and Technology Experience:
Strong Python programming (data handling, OOP, automation frameworks)
SQL (Advanced) – complex joins, window functions, performance tuning
ETL & Data Pipeline Testing experience
Automation testing mindset (not manual-heavy profiles)
Experience with large datasets (millions+ records)
Data & Big Data Technologies
Experience with at least one:
Apache Spark / PySpark
Hadoop ecosystem
Cloud data warehouses (Snowflake, Redshift, BigQuery, Synapse)
Data formats: Parquet, Avro, JSON, CSV
Test Automation & DevOps
PyTest, unittest, or similar Python testing frameworks
CI/CD tools: GitHub Actions, Jenkins, GitLab CI (any one)
Version control using Git
Linux/Unix shell scripting basics
Cloud & Modern Data Stack (Preferred)
AWS, Azure, or GCP (any one)
Databricks experience is a plus
Experience testing APIs & data services (REST)
Hands-on data engineering experience
Knowledge of data modeling (Kimball / dimensional modeling)
Experience with data governance, metadata, or data quality tools
Exposure to real-time/streaming data (Kafka, Kinesis)
Experience with monitoring data pipelines
Strong problem-solving and debugging skills
Ability to own data quality end-to-end
Comfortable working with cross-functional teams
Curious mindset with willingness to learn data engineering deeply
Excellent communication skills (US client-facing)
Bachelor’s degree in computer science, Engineering, or related field
5+ years total experience in data testing, automation, or backend/data-heavy systems
Prior SDET or Quality Engineering background strongly preferred
Our client is a leading IT Industry, and we are currently interviewing to fill this and other similar contract positions. If you are interested in this position, please apply online for immediate consideration.
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