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Sql

Hampton,VA

1185 Sql jobs in Hampton,VA

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BOOZ, ALLEN & HAMILTON Logo

BOOZ, ALLEN & HAMILTON - Norfolk, VA

Operations Research Analyst
~ 24 min OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit
Data Engineer

Family Dollar

Chesapeake, VA 23322

Paid Relocation to Chesapeake, VA

~ 37 min Onsite

Projected Salary Range: $95,000 - $118,500
10% annual bonus opportunity
We handle relocation for anyone interested outside of the Hampton Roads, VA area
Full-time
Full time
Candidates must be authorized to work in the United States without the need for current or future visa sponsorship.
Bachelor's degree or higher in Computer Science, Engineering, or a related field.
3+ years of experience in data engineering or data analytics.
Strong understanding of RDBMS concepts with 3+ years of advanced SQL and data analysis experience.
2+ years of experience with Linux command‑line tools and scripting.
3+ years of Python development experience with expert‑level proficiency.
1+ year working with Big Data processing frameworks and tools.
Hands‑on experience with GCP services such as Cloud Storage, Dataflow, Pub/Sub, and BigQuery.
Strong proficiency in SQL, Python, Linux shell scripting, and data modeling.
Solid knowledge of data modeling techniques
Ability to analyze source systems and transform data to meet target data model requirements.
Experience working with large‑scale data warehouses (10+ TB) and high‑volume ETL/ELT workloads (50M+ records/day).
Demonstrated experience delivering end‑to‑end technical solutions within enterprise BI/Data Warehousing environments.
Experience with performance tuning and optimization across the data delivery pipeline—from ingestion through analytics.
Experience working in a Scrum/Agile environment and tools such as Jira.
Experience migrating data of various formats (JSON, delimited files, APIs, real‑time feeds) into Google BigQuery is strongly preferred.
Experience working with a data science workbench or ML development environment.
Familiarity with data engineering aspects of machine learning pipelines (e.g., data prep, splitting, feature engineering, scoring)
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