Data Analyst

Strategic Staffing Solutions; McLean (VA); On-site; USD 83,000 - 131,000; Full time

Job summary

Strategic Staffing Solutions, Inc. is seeking a Senior Data Analyst / Data Engineer for a contract engagement in the United States. The role focuses on optimizing SQL and Python pipelines, consolidating scripts, and designing new datasets to support business reporting and analytics.

The ideal candidate will work independently with ambiguous data, improve data quality, and deliver scalable, reusable data solutions while collaborating with stakeholders and documenting processes.

Qualifications

• Hands-on SQL and Python development experience required.
• Experience consolidating, simplifying, and optimizing data pipelines.
• Experience building and deploying new datasets from scratch.
• Ability to work with ambiguous or unstructured data requirements.
• Strong data analysis, troubleshooting, and problem-solving skills.
• Ability to work independently and with cross-functional teams.

Responsibilities

• Analyze, consolidate, and optimize existing SQL and Python scripts and data pipelines.
• Design, develop, and implement new datasets to support reporting and analytics.
• Work with ambiguous data to identify patterns, resolve inconsistencies, and establish reliable structures.
• Improve data quality, consistency, and integrity across datasets.
• Collaborate with stakeholders to translate data needs into technical solutions.
• Troubleshoot data issues and streamline workflows.
• Document data transformations and pipeline logic.

Skills

SQL & Python

Data pipelines optimization

Dataset development

Ambiguous data handling

Data analysis & troubleshooting

Independent & cross-functional

Tools

Databricks

OneLake

OneStream

Git

Job description

Senior Data Analyst / Data Engineer

Job Type: Contract
Location: TBD

Position Overview

We are seeking an experienced Senior Data Analyst / Data Engineer with strong SQL and Python skills to optimize existing data pipelines, consolidate scripts, and develop new datasets to support business needs.

The ideal candidate is a hands-on technical professional who can work independently with ambiguous or loosely defined data, identify opportunities for improvement, and deliver scalable, reusable, and high-quality data solutions.

Key Responsibilities

• Analyze, consolidate, and optimize existing SQL and Python scripts and data pipelines to improve efficiency, performance, and reusability.

• Design, develop, and implement new datasets to support business reporting, analytics, and operational requirements.

• Work with ambiguous, incomplete, or loosely defined datasets to identify patterns, resolve inconsistencies, and establish reliable data structures.

• Improve data quality, consistency, and integrity across existing and newly developed datasets.

• Collaborate with business and technical stakeholders to clarify data requirements and translate business needs into technical solutions.

• Troubleshoot data issues, streamline workflows, and implement sustainable improvements to data processes.

• Document data transformations, pipeline logic, and development processes.

Required Qualifications

• Strong hands-on SQL and Python development experience.

• Proven experience consolidating, simplifying, and optimizing existing scripts and data pipelines.

• Experience building and deploying new datasets from the ground up.

• Demonstrated ability to work with ambiguous, unstructured, or poorly defined data requirements.

• Strong data analysis, troubleshooting, and problem-solving skills.

• Ability to work independently and collaborate with cross-functional teams.

Preferred Qualifications

• Experience with Databricks, Microsoft OneLake, or OneStream.

• Experience using Git or similar version control tools.

• Familiarity with Capital One datasets, data platforms, or enterprise data environments.

• Previous experience in financial services or banking.

Ideal Candidate

We welcome candidates from both Data Analyst and Data Engineer backgrounds, provided they have strong SQL and Python expertise, hands-on pipeline optimization experience, and the ability to develop reliable datasets in environments with unclear or evolving requirements.