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Contract Databricks Developer Jobs in Connecticut

Deloitte

Senior Data Engineer

Stamford, CT · Hybrid

$113K - $153K/yr

Databricks (Delta Lake, Unity Catalog, Workflows) * Apache Airflow * Git / Azure DevOps * Deep ... Collaborate with different teams on data contracts and schema agreements * Lead design and ...

Deloitte

Senior Data Engineer

Hartford, CT · Hybrid

$106K - $145K/yr

Databricks (Delta Lake, Unity Catalog, Workflows) * Apache Airflow * Git / Azure DevOps * Deep ... Collaborate with different teams on data contracts and schema agreements * Lead design and ...

GE Aerospace

Software Engineer AI/ML

Norwalk, CT

$114K - $138K/yr

... contracts, and operations. We're looking for an AI Engineer to help transform GE Aerospace ... AWS, Visual Studio, Databricks, GitHub, etc. * Experience building REST APIs (FastAPI, Flask) for ...

All JobsContract Databricks Developer JobsContract Databricks Developer Jobs in Connecticut

Contract Databricks Developer information

What is a Contract Databricks Developer?

A Contract Databricks Developer is a data engineering professional hired on a temporary or project basis to develop, optimize, and maintain data pipelines and analytics solutions using the Databricks platform. They work with cloud data technologies, Spark, and big data frameworks to support organizations in managing large-scale data processing and analytics tasks. Their responsibilities often include building ETL workflows, collaborating with data scientists, and ensuring data quality and performance in data-driven projects.

What are some common challenges faced by Contract Databricks Developers when starting a new project?

As a Contract Databricks Developer joining a new project, you may encounter challenges such as quickly understanding the existing data architecture, adapting to the client's specific workflow, and ensuring seamless integration with their cloud infrastructure (often Azure or AWS). You’ll also need to align with established data governance and security protocols while collaborating with data engineers, analysts, and business stakeholders. Effective communication and proactive documentation are key to overcoming these hurdles and delivering value efficiently within the contract period.

What is the difference between Contract Databricks Developer vs Data Engineer?

AspectContract Databricks DeveloperData Engineer
Primary FocusDeveloping and optimizing data pipelines using Databricks platformDesigning, building, and maintaining scalable data architectures
Skills & CertificationsProficiency in Spark, SQL, Python, Databricks platform, and cloud servicesKnowledge of ETL processes, SQL, Python, cloud platforms, and data modeling
Work EnvironmentProject-based, often remote, with a focus on Databricks environmentsVaries from in-house teams to consulting, working on large-scale data systems

While both roles require expertise in data processing and cloud platforms, a Contract Databricks Developer specializes in building data solutions specifically within the Databricks environment, whereas a Data Engineer has a broader scope in designing and managing overall data infrastructure across various tools and platforms.

What are the key skills and qualifications needed to thrive as a Contract Databricks Developer, and why are they important?

To excel as a Contract Databricks Developer, you need strong expertise in data engineering, big data analytics, and proficiency in programming languages like Python or Scala, typically backed by relevant experience or a degree in computer science. Familiarity with Databricks, Apache Spark, cloud platforms (such as Azure or AWS), and certifications like Databricks Certified Associate Developer are commonly required. Excellent problem-solving, adaptability, and communication skills help you collaborate with clients and teams to deliver tailored data solutions. These competencies are crucial for building scalable data pipelines and efficiently managing large datasets in dynamic project environments.
What are the most commonly searched types of Databricks Developer jobs in Connecticut? The most popular types of Databricks Developer jobs in Connecticut are:
What are popular job titles related to Contract Databricks Developer jobs in Connecticut? For Contract Databricks Developer jobs in Connecticut, the most frequently searched job titles are:
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What cities in Connecticut are hiring for Contract Databricks Developer jobs? Cities in Connecticut with the most Contract Databricks Developer job openings:
Contract Databricks Developer jobs near you
Staff Data Platform Architect (Databricks)

Staff Data Platform Architect (Databricks)

Aquent

Hartford, CT • On-site

$55 - $57/hr

Temporary

Posted 29 days ago

Job description

Placement Type:
Temporary
Salary:
$55-57 Hourly
$55 - 57 / hourly as W2
Start Date:
Jun 29, 2026
Staff Data Platform Architect (Databricks)
Hartford, CT, hybrid (on-site 3 days per week)
Department: Data & Analytics Platform
Business Unit: Infrastructure and Cloud Services
Reports To: Senior Director, Data Platform
Role Overview
We are seeking a Staff Data Platform Architect to serve as the primary technical consultant and strategist for our enterprise Databricks ecosystem. This is a high-impact, senior individual contributor role focused on driving technical excellence, automation, and fiscal efficiency.
Unlike a traditional administrator, you will act as an internal consultant to our extensive Databricks team, providing the blueprint for scalable pipelines, advanced automation, and long-term capacity forecasting. You will bridge the gap between complex infrastructure (Unix/Linux) and modern AI/ML workflows, ensuring our platform is both cutting-edge and cost-effective.
Key Responsibilities
Strategic Consultation & Architecture
  • Act as the Technical Authority for Databricks, advising engineering teams on Unity Catalog governance, workspace topology, and complex migration patterns.
  • Consult on the design of high-performance data pipelines, specifically optimizing Delta Live Tables (DLT) and structured streaming for scale.
  • Partner with teams using Ab Initio and Fivetran to ensure seamless integration and architectural alignment across the multi-platform ecosystem.

Platform Optimization & Financial Forecasting
  • Capacity Planning: Own the forecasting of DBU consumption and partner with leadership on multi-year contract utilization and commitment management.
  • Cost Engineering: Design and implement sophisticated cost-attribution models (chargeback/showback) and proactively identify "leaks" in compute spend.
  • Performance Tuning: Define enterprise standards for Z-ordering, partitioning, and compute strategy to maximize performance-per-dollar.

Advanced Automation & AI Operations
  • Architect "self-healing" infrastructure through Python and Bash automation, reducing manual toil for the wider engineering team.
  • Consult on the operationalization of ML models, leveraging MLflow and Model Serving to move experiments into production.
  • Guide the integration of Generative AI and LLM-backed workflows into the standard data engineering lifecycle.

Infrastructure & Linux Engineering
  • Provide deep-tier expertise for the Unix/Linux environments underpinning our compute nodes.
  • Develop advanced automation scripts for cluster lifecycle management, monitoring, and security hardening.
Required Qualifications
  • Experience: 7+ years in Data Engineering/Platform roles, with at least 4 years of deep architectural experience in Databricks.
  • The "Consultant" Mindset: Proven ability to advise multiple teams, influence technical roadmaps, and communicate complex trade-offs to senior leadership.
  • Technical Depth: Mastery of Unity Catalog, Delta Lake, and PySpark.
  • Systems Expertise: Strong proficiency in Unix/Linux systems administration and shell scripting (Bash) for infrastructure automation.
  • Financial Acumen: Experience managing cloud consumption (DBUs), forecasting usage, and implementing cost-governance tools.
  • Tooling: High proficiency with Git-based CI/CD and experience in Oracle environments.
Preferred Qualifications
  • Hands-on experience with Infrastructure-as-Code (Terraform/Ansible) for Databricks provider.
  • Exposure to Ab Initio or Fivetran in a large-scale enterprise environment.
  • Background in highly regulated industries (e.g., Finance or Insurance).

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