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Step Functions Data Jobs

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Today

Senior Data Engineer

Steampunk McLean, VA

McLean, VA

Today

$140k - $180k/yr Full time Senior Apache Airflow AWS

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Job Description

Steampunk is hiring a Senior Data Engineer (onsite) to design and deliver enterprise-grade data platforms, services, and pipelines using Databricks.

Responsibilities

Lead and architect data migrations using Databricks, with emphasis on performance, reliability, and scalability
Assess and understand existing ETL jobs, workflows, data marts, BI tools, and reports
Respond to technical inquiries related to customization, integration, enterprise architecture, and feature/functionality of data products
Support an Agile software development lifecycle
Contribute to the growth of the AI & Data Exploitation Practice
Inspect existing data pipelines, identify their purpose and functionality, and re-implement them efficiently in Databricks

Requirements

Current ICE US Public Trust Clearance (Full Background Investigation)
Ability to hold a position of public trust with the US government
5–7 years industry experience coding commercial software and a passion for solving complex problems
5–7 years direct experience in Data Engineering, including experience with:
- Big data tools: Databricks, Apache Spark, Delta Lake, etc.
- Relational SQL (preferably T-SQL; alternatively pgSQL, MySQL)
- Data pipeline and workflow management tools: Databricks Workflows, Airflow, Step Functions, etc.
- AWS and Azure cloud services (for example: Databricks on AWS, S3, EC2, RDS)
- Object-oriented/object function scripting languages: PySpark/Python, Java, C++, Scala, etc.
- Data lakehouse architecture and Delta Lake/Apache Iceberg
Advanced working knowledge of SQL, including query authoring and optimization, plus working familiarity with a variety of databases
Experience manipulating, processing, and extracting value from large, disconnected datasets
Experience manipulating structured and unstructured data
Experience architecting data systems (transactional and warehouses)
Experience with SDLC, CI/CD, and operating in dev/test/prod environments
Commitment to data governance
Experience working in an Agile environment
Experience supporting project teams of developers and data scientists building web-based interfaces, dashboards, reports, and analytics/machine learning models
Plus: Experience with data cataloging tools such as Informatica EDC, Unity Catalog, Collibra, Alation, Purview, or DataZone

Technologies

Databricks
SQL, T-SQL, pgSQL, MySQL
PySpark, Python
Apache Spark
Delta Lake
Databricks Workflows, Airflow, Step Functions
AWS, Azure
S3, EC2, RDS
Java, C++, Scala
Data Lakehouse, Apache Iceberg
Informatica EDC, Unity Catalog, Collibra, Alation, Purview, DataZone
CI/CD, SDLC

Additional Information

Location: McLean, VA (onsite)
Salary: USD 140,000 - 180,000 per yearly
Minimum experience: 5 years

Identity Verification

During the application process, you are expected to be on camera during interviews and assessments
Steampunk reserves the right to take your picture to verify your identity and prevent fraud

Company Focus

Steampunk is a change agent in federal contracting, bringing new thinking to clients in Homeland and Federal Civil
Human-Centered delivery methodology emphasizes shared accountability for solving mission challenges

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4mo ago

Data Engineer, Analytics & Machine Learning Enablement

Keeper Security Remote 🌍 Remote

Remote

4mo ago Closed

Full time Analytics AWS Bigquery

This position is no longer accepting applications (closed Jun 6, 2026).

Job Description

Keeper Security is seeking a Data Engineer focused on building analytics data pipelines and ML-ready workflows. This remote role offers flexibility, with an optional hybrid schedule for candidates in California or Illinois. The position emphasizes collaboration with analysts and ML engineers to enable reliable analytics and modeling capabilities across the organization.

Responsibilities

Design and maintain ELT pipelines to ingest and transform data from core operational systems
Create analytics-ready data models to support reporting, KPIs, and downstream ML use cases
Collaborate with analysts and ML engineers to ensure data structures meet modeling and feature needs
Implement data quality checks, validation, and testing to ensure accuracy and reliability
Optimize data pipeline performance, scalability, and cost efficiency
Support data preparation and feature engineering workflows for machine learning initiatives
Document data models, transformations, and lineage to promote reuse and data literacy
Partner with security and platform teams to ensure data governance and privacy requirements are met

Requirements

3–5 years of experience in data engineering or backend data systems, SaaS experience preferred
Strong proficiency in SQL and experience designing analytics data models
Working knowledge of Python for data processing or pipeline orchestration
Experience with cloud data warehouses such as Amazon Redshift; Snowflake or BigQuery acceptable
Familiarity with AWS data services such as S3, Glue, Lambda, or Step Functions
Understanding of ELT best practices, data modeling, and schema design
Exposure to supporting machine learning workflows through data preparation or feature engineering
Knowledge of data security and privacy principles, including handling regulated data (PII, PHI)
Strong software engineering fundamentals, including version control, testing, and CI/CD practices
Bachelor's degree in Computer Science, Engineering, Statistics, or a related field
Due to FedRAMP requirements, candidates must be a U.S. Person

Technologies

Python
SQL
Amazon Redshift
Snowflake
BigQuery
S3
Glue
Lambda
Step Functions
dbt

Benefits

Medical, Dental & Vision (Inclusive of domestic partnerships)
Employer Paid Life Insurance & Employee/Spouse/Child Supplemental life
Voluntary Short/Long Term Disability Insurance
401k (Roth/Traditional)
A generous PTO plan that celebrates your commitment and seniority (including paid Bereavement/Jury Duty, etc)
Above market annual bonuses

Keeper Candidate Privacy Notice

Keeper collects and uses data throughout the recruitment process to assess your qualifications and manage interviews. Data may be provided by you, generated during the process, or obtained from others.

Data We Collect: Contact details, CV/resume, cover letter; employment history, qualifications, work eligibility; application responses and uploaded documents
Data We Generate: Interview notes, assessments, communications; scheduling information
Information From Others: Referrals, public professional profiles, background verification (post offer)
Voluntary Diversity Information: Optional data on race/ethnicity, gender, disability status, veteran status to comply with EEOC requirements
How We Use Your Data: Assess suitability; manage interviews; consider for other roles; comply with employment laws
Legal Basis: Legitimate interests; contractual steps; legal/regulatory compliance
Sharing: Internal teams and third-party service providers; diversity data is not shared with hiring managers
Third Party Safeguards: Contracts to protect data with appropriate safeguards
International Transfers: Data may be accessed globally with safeguards in place
Security: Technical and organizational measures to protect data
Retention: Data kept for 24 months from last activity, with exceptions for consent or hire
Your Rights: Access, correction, deletion, objection, data portability, complaint
Automated Decisions: No hiring decisions are made solely by automated processing
Contact: privacy@keepersecurity.com

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Senior Data Engineer

Data Engineer, Analytics & Machine Learning Enablement

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