Senior Data Engineer

Dynamo Technologies
Vienna, VA, United States
18 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
6 years minimum
Compensation
$100,000.0 - $125,000.0
Working hours
Regular working hours

Tech stack

Amazon Web Services Business Analytics Applications Data Analysis Automation of Tests Cloud Database Information Systems Databases Continuous Delivery Continuous Integration Customer Data Management Information Engineering Data Governance
+34 more
Data Integration Extract Transform Load (ETL) Data Structures Data Warehousing Database Development Linux DevOps Web Development Document-Oriented Databases Python (Programming Language) PostgreSQL Meta-Data Management Microsoft SQL Server Windows Servers DataOps Salesforce.Com Software Deployment Software Engineering SQL Stored Procedures Data Streaming Technical Data Management Systems Web Applications Enterprise Data Management Data Processing Scripting Freeform SQL Enterprise Software Applications Cloud Platform System Backend Information Technology Data Analytics Data Management Data Delivery Data Pipelines

Job description

Dynamo Technologies LLC is seeking a Senior Data Engineer to support the Consumer Financial Protection Bureau (CFPB). The selected candidate will provide technical expertise in data engineering, data operations, data quality, analytics, and data management. This role will support the design, development, operation, and maintenance of data pipelines, data products, ETL processes, and data warehouse solutions in support of CFPB mission requirements., The ideal candidate will have strong hands-on experience with Python or R, complex SQL development, enterprise databases, Linux/UNIX environments, and data engineering practices. Experience supporting cloud-based data environments, particularly Amazon Web Services (AWS), is highly desirable., * Design, develop, maintain, and troubleshoot data pipelines and data products supporting enterprise analytics and reporting.

  • Develop and maintain ETL processes to extract, transform, cleanse, validate, and load data from multiple sources.
  • Use Python or R to support data analytics, data operations, automation, backend development, and data pipeline activities.
  • Write, optimize, and troubleshoot complex SQL queries using enterprise databases such as PostgreSQL and Microsoft SQL Server.
  • Develop and maintain data warehouse solutions, including data structures, transformations, and operational processes.
  • Support data quality initiatives by identifying data issues, performing root cause analysis, and implementing solutions to improve data accuracy, consistency, and reliability.
  • Monitor and troubleshoot data pipelines, ETL processes, databases, and other data operations to ensure reliable and timely data delivery.
  • Develop database stored procedures, functions, and other database objects to support data processing and application requirements.
  • Support data integration efforts across enterprise applications and data sources.
  • Work in Linux/UNIX and Windows server environments to support data operations, application deployments, and troubleshooting.
  • Apply DevOps principles and practices to data engineering and application development processes.
  • Collaborate with stakeholders to gather requirements, analyze business processes, and translate mission needs into scalable technical data solutions.
  • Support the development and maintenance of web applications and other technical solutions that enable data analytics and data-driven decision-making.
  • Support integration and analysis of Salesforce data and other enterprise data sources.
  • Document data processes, technical requirements, data flows, pipelines, and operational procedures.
  • Identify opportunities to improve data engineering processes, automation, performance, and reliability.
  • Collaborate with developers, analysts, business stakeholders, and other technical teams throughout the software and data development lifecycle.

Requirements

  • Hands-on professional experience with Python or R for data analytics, data operations, automation, backend development, or data pipeline development.
  • Strong proficiency writing and optimizing complex SQL queries using enterprise databases such as PostgreSQL or Microsoft SQL Server.
  • Experience developing and supporting ETL processes and data pipelines.
  • Experience with data warehouse development and operations.
  • Experience working in both Linux/UNIX and Windows environments.
  • Knowledge of DevOps principles and practices as applied to data engineering and software development.
  • Experience troubleshooting data operations, data pipelines, data quality issues, and backend data processes.
  • Strong analytical, problem-solving, and technical documentation skills.
  • Ability to gather requirements and translate business and operational needs into technical data solutions.
  • Ability to work collaboratively with technical teams, business stakeholders, and end users.

Nice-to-Have Skills:

  • Experience developing and operating data pipelines and data products in Amazon Web Services (AWS) or other cloud environments.
  • Experience creating database stored procedures and functions.
  • Experience developing web applications or backend services that support data analytics.
  • Experience working with Salesforce data and Salesforce integrations.
  • Experience with cloud-based data engineering, data warehouse, or analytics platforms.
  • Experience with additional programming or scripting languages used for data engineering.
  • Experience with automated testing, continuous integration/continuous deployment (CI/CD), and DevOps tools.
  • Experience supporting federal government or financial regulatory organizations.
  • Familiarity with data governance, metadata management, and enterprise data quality practices., * Bachelor’s degree or advanced degree in Information Systems, Computer Science, Data Science, Mathematics, Statistics, Operations Management, Engineering, or a related technical or quantitative field is highly preferred.
  • Minimum of six (6) years of relevant professional experience supporting data engineering, data operations, data quality, data analytics, data management, or related technical functions.
  • Equivalent combination of education and relevant professional experience may be considered.

Benefits & conditions

Salary Range: The salary range for this position represents Dynamo’s good-faith estimate of the compensation expected to be offered at the time of posting. Actual compensation will be determined based on several factors, including, but not limited to, the responsibilities of the role, the candidate’s experience, skills, education, work location, and internal equity.

$100k-$125k annually

Dynamo is a full lifecycle digital transformation company providing best-in-class technology and mission support services to our clients. Dynamo’s mission is to lead the digital transformation industry and provide best-in-class solutions for our clients with a truly human touch.

We leverage industry leading practices to empower our clients, ultimately providing them with the necessary tools, knowledge, and information required to successfully achieve their strategic goals, while optimizing their operations.

Through our partnerships, boldness, and authenticity, Dynamo goes against the grain of a traditional government contracting company by providing top-caliber team members, delivering quality results, and always exceeding expectations.

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