The role

We are seeking a highly skilled Data Engineer who also possesses strong Quality Assurance (QA) knowledge. This role is primarily focused on data engineering and development work, but the candidate will also support QA activities to ensure the delivery of high-quality data solutions. The ideal candidate is versatile, detail-oriented, and capable of contributing across the data lifecycle.

What will you do?

• Development & Data Engineering (Primary Focus)

• Design, develop, and maintain scalable data pipelines and ETL processes using Python and PySpark.

• Implement data models, transformations, and integrations for structured and semi-structured data (CSV, JSON, XML).

• Optimize performance for large-scale data processing and storage.

• Contribute to Test Automation Framework development, ensuring reusable and scalable automation components.

• Support Group Intake Automation by translating business needs into technical workflows and backend solutions.

• Enhance BotData, a smart data generation tool for synthetic data creation and validation.

• Write, test, and optimize Python scripts for automation, data processing, and transformation tasks.

• Collaborate with senior developers to troubleshoot issues, implement improvements, and follow best practices in coding and automation.

• Work with cloud-native development efforts using platforms like GCP (Airflow orchestration, data storage).

• Use Git/GitHub/GitLab for version control, managing branches, pull requests, and collaborative workflows.

• Explore emerging technologies such as GenAI, ML, and data privacy tools, contributing to innovation-driven proof-of-concept projects.

What do you need to succeed?

• Quality Assurance (Secondary Focus)

• Assist in creating and executing test plans, test cases, and automation scripts for data validation.

• Perform functional, regression, and integration testing on data workflows.

• Ensure adherence to data quality standards and help identify defects early in the cycle.

• Support CI/CD pipelines with automated testing using tools like Jenkins, GitHub Actions, or Azure DevOps.

• Strong proficiency in Python, PySpark, and SQL.

• Solid understanding of data engineering principles, ETL design, and best practices.

• Experience with data manipulation using pandas and handling structured/semi-structured data (CSV, JSON, XML).

• Knowledge of software development principles, version control (Git), and Agile/Scrum practices.

• Familiarity with QA methodologies, tools, and automation frameworks (e.g., PyTest).

• Understanding of CI/CD tools and workflows.

• Excellent problem-solving skills, attention to detail, and ability to work independently and proactively.

• Exposure to Apache Spark, PySpark, or Hadoop ecosystem tools.

• Familiarity with cloud platforms (AWS, Azure, or GCP).

• Experience with REST APIs, YAML, or data transformation tools.

• Interest in test automation, data engineering, or DevOps practices.

• Awareness of CI/CD tools like Jenkins, GitHub Actions, or Azure DevOps.

• Curiosity about GenAI, machine learning, or data privacy concepts

What's in it for you?

• We have an inclusive and collaborative working environment that encourages creativity and curiosity and celebrates success
• We provide you with the tools and technology needed to create meaningful customer experiences
• You'll get to work with and learn from diverse industry leaders, who have hailed from top technology companies around the world
• We hire you for your talent — not just a job — so you can grow with us. We’ll equip you for success not only in your role, but also in your career as a whole
• Dress codes don't apply here: being comfortable does
• Access to thousands of online and in-person courses so you can hone your current skills, or learn new ones
• A competitive rewards package that includes a base salary, a performance bonus, company matching programs on pension and profit sharing, paid vacation, personal & sick days, medical, vision, and dental and much more!