Data Engineer Job at Tential Solutions, Washington DC

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  • Tential Solutions
  • Washington DC

Job Description

Join to apply for the Data Engineer role at Tential Solutions

Were partnering with a Big 4 consulting firm to add a Data Engineer to their team supporting a major banking and credit organization. This role focuses on building and optimizing scalable, cloud-based data pipelines using Python, Java, SQL, AWS, Spark, Databricks, and EMR . Youll work across consulting and client teams to deliver reliable data solutions that power analytics, risk, and credit decisioning use cases. This position is fully remote .

Responsibilities


  • Design, build, and maintain scalable data pipelines and ETL/ELT processes using Python, Java, and SQL.
  • Develop and optimize distributed data processing workloads using Spark (batch and/or streaming) on AWS.
  • Build and manage data workflows on AWS, leveraging services such as EMR, S3, Lambda, Glue, and related components as appropriate.
  • Use Databricks to develop, schedule, and monitor notebooks, jobs, and workflows supporting analytics and data products.
  • Implement data models and structures that support banking/credit analytics, reporting, and downstream applications (e.g., risk, fraud, portfolio, customer insights).
  • Monitor, troubleshoot, and tune pipeline performance, reliability, and cost in a production cloud environment.
  • Collaborate with consultants, client stakeholders, data analysts, and data scientists to understand requirements and translate them into technical solutions.
  • Apply best practices for code quality, testing, version control, and CI/CD within the data environment.
  • Contribute to documentation, standards, and reusable components to improve consistency and speed across the data engineering team.


Required Qualifications
  • Strong hands?on experience with Python and Java for data engineering, ETL/ELT, or backend data services.
  • Advanced SQL skills, including complex queries, performance tuning, and working with large, relational datasets.
  • Production experience on AWS, ideally with services such as EMR, S3, Lambda, Glue, IAM, and CloudWatch.
  • Practical experience building and optimizing Spark jobs (PySpark, Spark SQL, or Scala).
  • Hands?on experience with Databricks (notebooks, clusters, jobs, and/or Delta Lake).
  • Proven experience building and supporting reliable, performant data pipelines in a modern cloud environment.
  • Solid understanding of data warehousing concepts, data modeling, and best practices for structured and semi?structured data.
  • Experience working in collaborative engineering environments (Git, code reviews, branching strategies).
  • Strong communication skills and comfort working in a consulting/client?facing environment.


Preferred Qualifications (Nice To Have)
  • Experience in banking, credit, financial services, or highly regulated environments.
  • Background with streaming data (e.g., Spark Streaming, Kafka, Kinesis) and real?time or nearreal?time data processing.
  • Familiarity with orchestration tools (e.g., Airflow, Databricks jobs scheduler, Step Functions).
  • Experience supporting analytics, BI, or data science teams (e.g., building curated datasets, feature stores, or semantic layers).


Seniority Level: Entry level. Employment type: Contract. Job function: Information Technology.

Remote: Yes

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Job Tags

Contract work, Remote work,

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