Data Pipeline Engineer

Outstanding long-term contract opportunity! A well-known Financial Services Company is looking for a Data Pipeline Engineer in Irving TX or Charlotte NC

Work with the brightest minds at one of the largest financial institutions in the world. This is a long-term contract opportunity that includes a competitive benefit package! Our client has been around for over 150 years and is continuously innovating in today's digital age. If you want to work for a company that is not only a household name, but also truly cares about satisfying customers' financial needs and helping people succeed financially, apply today.

Contract Duration: starting at 6 months with possible extensions or full time conversion

We are seeking an experienced Data Pipeline Engineer
to design, architect, and maintain scalable data pipelines that support reporting and downstream applications. The ideal candidate will bring strong expertise in cloud-based and open-source data technologies, modern data lake architectures, and data engineering best practices.

• Expertise in SQL
  for data analysis, transformation, and performance tuning.
• Strong hands-on experience with Python and Spark
  for large-scale data processing.
• Experience with data pipelining and orchestration tools
  (e.g., Airflow, Cloud Composer, or equivalent).
• Solid understanding of databases, data warehousing, and
  data lake architectures
  .
• Proven experience designing and architecting data pipelines for analytics and reporting.
• Experience working with legacy ETL tools such as
  SSIS, Ab Initio, SAS
  , or equivalent.
• Strong analytical, critical thinking, and problem-solving skills.
• Ability to adapt quickly to evolving technologies and business requirements.

• Expertise in cloud platforms, with
  Google Cloud Platform (GCP)strongly preferred.
• Experience building cloud-native data lake solutions using open-source technologies.

• Design, architect, and implement scalable data pipelines for reporting and downstream applications using open-source tools and cloud platforms.
• Build and support cloud-based
  data lake architectures
  for both operational and analytical data stores.
• Apply strong database, SQL, and reporting concepts to design efficient, high-performance data solutions.
• Develop data processing and transformation logic using
  Python and Spark
  .
• Work with and interpret legacy ETL code and workflows from tools such as
  SSIS, Ab Initio, SAS
  , and similar technologies to support modernization and migration initiatives.
• Utilize modern
  data pipelining and orchestration tools
  to automate, monitor, and optimize data workflows.
• Troubleshoot data pipeline issues, ensure data quality, and optimize performance and reliability.
• Demonstrate critical thinking, adaptability to change, and strong problem-solving skills.