Data Engineer

Job Family: Data Science & Analysis Travel Required: Up to 10% Clearance Required: Ability to Obtain Public Trust

What You Will Do: Our consultants on the Defense & Security AI & Data team help clients maximize the value of their data and automate business processes. This high performing team works with clients to implement the full spectrum of data analytics and data science, from data querying and wrangling to data engineering, to data visualization, dashboarding, and business intelligence (BI), to predictive analytics, machine learning (ML), and artificial intelligence (AI). Our services enable our clients to define their information strategy, enable mission critical insights and data-driven decision making, reduce cost and complexity, increase trust, and improve operational effectiveness.

Conduct ETL and data quality analysis using various technologies (i.e., Python, Databricks) in cloud-based databases and ETL architecture.

Develop intuitive, attractive, and interactive data visualizations using large data sets to create dashboards, using tools such as Tableau and Power BI, for a diverse set of users with varying technical capabilities.

Partner with ISSOs, system owners, and Agile delivery teams to define data requirements, curate datasets, and operationalize dashboards for mission decision-making.

Operate within CI/CD and DevSecOps practices to version experiments, automate data/feature pipelines, and validate models in controlled environments.

Communicate findings in plain language and produce clear visualizations and documentation that align to stakeholder needs.

What You Will Need: Must be able to OBTAIN and MAINTAIN a Federal or DHS "PUBLIC TRUST"; candidates must obtain approved adjudication of their PUBLIC TRUST prior to onboarding with Guidehouse. Candidates with an ACTIVE PUBLIC TRUST or SUITABILITY are preferred.

Bachelor’s degree THREE (3) or more years’ experience as a Data Security Analyst or equivalent knowledge.

FOUR (4) or more years’ experience in data analytics with large data sets.

Experiencedesigning and developing databases with Structured Query Language (SQL) and performing complex queries.

Experience developing complex data pipelines and extract – transform – load (ETL) processes.

Expeirence moving and manipulating data of different types and file types using Python.

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