Lakehouse Engineer and Analyst, Mid

Booz Allen Hamilton

Confirmed live today High trust

Quick summary

Work type
On-site
Location
McLean, VA
Salary
$77,600–$176,000 / yr
Posted
3 days ago
Freshness
Confirmed live today
Nearby
99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $160k
This role $127k
$64k most similar roles pay here $207k

This role pays less than 65% of similar roles. Most pay $126,800–$193,000 — the shaded band above. At the midpoint, this role pays about $127k versus about $160k for comparable roles.

Based on 240 similar postings.

Employer

About Booz Allen Hamilton

Booz Allen Hamilton is a management and technology consulting firm that provides analytics, digital, engineering, and cybersecurity solutions primarily to U.S. government agencies and commercial clients. Industry: Management & Technology Consulting

Booz Allen Hamilton currently has 770 open roles on FindRole.

Listed pay typically runs $86,800–$198,000 across 746 roles with salary data.

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At a glance

TL;DR · Lakehouse Engineer and Analyst, Mid

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The Databricks Lakehouse Engineer and Analyst, Mid role involves building a modern Databricks Lakehouse environment to support real-time fraud detection, investigative analytics, and AI-driven risk insights for a government agency client. You will perform hands-on work across data engineering, platform configuration, functional analysis, governance, and model integration. The day-to-day responsibilities include managing fraud analytics enablement and coordinating with technical and non-technical stakeholders. To succeed, you must possess expertise in Databricks, Delta Lake, PySpark, structured streaming, and medallion architecture. You will also utilize Unity Catalog for governance and access controls while applying text mining or machine learning techniques. The role requires proficiency in Python, SQL, R, NoSQL, and distributed computing tools like Spark, Kafka, and Hadoop to solve complex problems involving fraud analytics, risk scoring, and anomaly detection within a federal environment.

Skills

Databricks Delta Lake PySpark SQL Python R NoSQL Spark Kafka Hadoop Hive EMR Unity Catalog NLP Machine Learning AI Plotly Seaborn ggplot2 MapReduce

What you'll do

  • Build and maintain a modern Databricks Lakehouse environment for real-time fraud detection and risk insights.
  • Develop data pipelines using PySpark, Delta Lake, and medallion architecture to process structured and unstructured data.
  • Implement Unity Catalog governance and access controls within the Databricks platform.
  • Integrate machine learning models and NLP techniques into existing data workflows.
  • Perform text mining and advanced analytics to support fraud investigation and risk scoring.
  • Manage technical infrastructure for distributed data processing and streaming.
  • Coordinate with fraud operations and technical stakeholders to translate requirements into technical solutions.

What we're looking for

  • 4+ years of experience in data engineering, analytics engineering, or ML engineering.
  • Experience with Databricks, Delta Lake, PySpark, structured streaming, and medallion architecture.
  • Knowledge of Unity Catalog governance, access controls, text mining, and ML/AI/NLP techniques.
  • Experience supporting fraud analytics, risk scoring, or anomaly detection.
  • 3+ years of experience developing algorithms using R, Python, SQL, or NoSQL (preferred).
  • 3+ years of experience with distributed data tools like MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL (preferred).
  • Bachelor’s degree.

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