Lenmar Consulting Inc.

Education Management

SeniorDataEngineer

Reston, Virginia, United States CONTRACT
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for mid candidates.

The Brief

“Senior Data Engineer at Lenmar Consulting Inc.. Skills: Data Quality, Data Engineering, AI-enabled tools. Ensure data is accurate, complete, timely, and trustworthy. Design data quality checks”

What You'll Achieve.

Improve confidence in data

Industry & Context.

Education Management
Problems you'll solve

Investigation; Analysis; Remediation; Structured Analysis; Troubleshoot Data

Eligibility Requirements

USC and GC only, No H1B, OPT, CPT EAD

What They're Looking For.

Must Have

BS degree in Engineering, Computer Science, or related field / equivalent experience, 10+ years of general experience in quality testing, SQL skills and experience writing complex queries, Professional experience in data engineering, analytics engineering, data quality, software Engineering, or a related field, Proficiency in Python or type script language, Experience designing or maintaining data quality checks, monitoring, alerting, or observability processes, Ability to investigate issues across systems, apply business logic, and translate ambiguous problems into structured analysis and action, Ability to support high-priority operational periods and respond effectively to production data issues

Nice to Have

Experience working with BI/reporting tools such as Tableau, QuickSight, or similar platforms is helpful

What You'll Do.

Ensure data is accurate

Design data quality checks

Implement data quality checks

Design monitoring processes

Implement monitoring processes

Design remediation processes

Implement remediation processes

Identify issues early

Reduce operational risk

Improve confidence in data

Automate data pipelines

Write testing workflows

How You'll Work.

Team & Collaboration

Cross-functional collaboration; Work with engineers; Work with analysts; Work with product teams; Work with business stakeholders; Work across technical teams; Work across non-technical teams

Communication Scope

Documentation; Collaboration

Full Job Description

Education USC and GC only on W2 – No H1B, OPT, CPT EAD at this time Data Quality Engineering & Monitoring (45%) Investigation, Analysis, & Remediation (35%) Governance, Documentation, & Team Success (20%) Skills: AI-enabled tools, AWS / Databricks, Tableau / QuickSight, Data Modeling, Data Structures, Typescript / Python, Copilot As a Senior Data Engineer, you'll help ensure that the data powering our products, reporting, and operational workflows is accurate, complete, timely, and trustworthy. You'll design and implement data quality checks, monitoring, and remediation processes across pipelines and platforms, working closely with engineers, analysts, product teams, and business stakeholders. Your work will help identify issues early, reduce operational risk, and improve confidence in the data used to support critical decisions and digital assessment experiences. This role blends hands-on technical investigation, automation, and cross-functional collaboration. About You * BS degree in Engineering, Computer Science, or related field / equivalent experience * 10+ years of general experience in quality testing * Strong SQL skills and experience writing complex queries to analyze, validate, and troubleshoot data across multiple systems. * Professional experience in data engineering, analytics engineering, data quality, software Engineering, or a related field with a strong focus on data investigation and validation. * Exposure to AI-assisted development tools (e.g., GitHub Copilot, Claude) and hands-on experience applying to build and deploy AI agents that automate data pipelines, write code and testing workflows. * Experience working with cloud data platforms and tools such as AWS, Redshift, Athena, Snowflake, Databricks, or similar technologies. * Proficiency in Python or type script language used for automation, testing, and data analysis. * Experience designing or maintaining data quality checks, monitoring, alerting, or observability processes for production datas

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