ZipRecruiter

Log In

1

Senior Databricks Data Engineer Jobs in Torrington, CT

Teamware Solutions

DATA Engineer

East Hartford, CT · On-site

$113K - $136K/yr

... a Senior Data Engineer to design, build, and optimize scalable data pipelines and warehouse ... Design and develop end-to-end data pipelines using Apache Spark and Databricks , following ...

Deloitte

Senior Data Engineer

Hartford, CT · Hybrid

$106K - $145K/yr

Design Databricks cluster policies, autoscaling configurations, and cost optimization strategies ... As an experienced Senior Data Engineer you will have the ability to share new ideas and collaborate ...

Pwc

Data Engineer - Senior Associate

Hartford, CT · On-site

$77K - $202K/yr

... Engineer - Senior Associate, you will focus on designing and building data infrastructure and ... Databricks Unified Data Analytics Platform for advanced data analytics and visualization ...

Pwc

Data Engineer - Manager

Hartford, CT

... Databricks Data Engineer Associate] is a plus - Designing and implementing thorough data architecture strategies that meet the current and future business needs - Developing and documenting data ...

The Whiteside Agency

Senior Data Engineer

Hartford, CT

$139K - $230K/yr

As a Senior Data Engineer you will accelerate growth and transformation of our analytics landscape ... Advanced knowledge of ETL tools like Abinitio & Databricks, AWS cloud platforms, programming ...

previous pagenext page

Showing results 21-40

All JobsDatabricks Data Engineer JobsSenior Databricks Data Engineer JobsSenior Databricks Data Engineer Jobs in Torrington, CT

Senior Databricks Data Engineer information

See Torrington, CT salary details

$58.7K

$124.9K

$181.1K

How much do senior databricks data engineer jobs pay per year?

As of Aug 7, 2026, the average yearly pay for senior databricks data engineer in Torrington, CT is $124,927.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,200.00 and $141,700.00 per year, depending on experience, location, and employer.

How does a Senior Databricks Data engineer typically collaborate with data scientists and analysts on large-scale projects?

A Senior Databricks Data Engineer works closely with data scientists and analysts to design, build, and optimize data pipelines that enable advanced analytics and machine learning initiatives. They often participate in cross-functional meetings to understand data requirements, translate them into scalable ETL processes, and ensure data quality and accessibility. Regular collaboration also involves troubleshooting data issues, optimizing Spark jobs for performance, and sharing best practices for data management. This close teamwork ensures that analytical teams have reliable, timely, and well-structured data to drive insights and decision-making.

What are the key skills and qualifications needed to thrive as a Senior Databricks Data engineer, and why are they important?

To thrive as a Senior Databricks Data Engineer, you need advanced expertise in data engineering concepts, big data technologies, and proficiency in programming languages like Python or Scala, usually backed by a bachelor's degree in computer science or a related field. Familiarity with Databricks, Apache Spark, cloud platforms (Azure, AWS, or GCP), and certifications like Databricks Certified Data Engineer are typically required. Strong problem-solving skills, effective communication, and the ability to collaborate across teams distinguish top performers in this role. These skills are essential to efficiently design scalable data solutions, optimize data workflows, and drive business insights in complex data environments.

What is the difference between Senior Databricks Data Engineer vs Data Engineer?

AspectSenior Databricks Data EngineerData Engineer
CredentialsTypically requires experience with Databricks, Spark, cloud platforms, and often certifications like Databricks Certified Data Engineer AssociateRequires knowledge of data pipelines, SQL, ETL tools, and often cloud platform experience, but less specialized in Databricks
Work EnvironmentWorks primarily within Databricks environment, focusing on big data processing and analyticsWorks across various data tools and platforms, including traditional ETL and cloud services
Industry UsageCommon in organizations leveraging Databricks for big data analytics and machine learningWidely used across industries for general data pipeline development and data management

The main difference is that a Senior Databricks Data Engineer specializes in using Databricks and Spark for big data solutions, often requiring specific certifications and experience. A Data Engineer has a broader focus on data pipeline development across various tools and platforms, with less emphasis on Databricks-specific skills.

What is a Senior Databricks Data engineer?

Senior Databricks Data Engineers are experienced professionals who design, develop, and optimize large-scale data processing pipelines using the Databricks platform. They work with big data technologies like Apache Spark, Delta Lake, and cloud platforms such as Azure or AWS. Their responsibilities include building and maintaining ETL processes, ensuring data quality, and collaborating with data scientists and analysts to deliver reliable, high-performance data solutions. As senior engineers, they also mentor junior team members and contribute to architectural decisions.
What are the most commonly searched types of Databricks Data Engineer jobs in Torrington, CT? The most popular types of Databricks Data Engineer jobs in Torrington, CT are:
What job categories do people searching Senior Databricks Data Engineer jobs in Torrington, CT look for? The top searched job categories for Senior Databricks Data Engineer jobs in Torrington, CT are:
Senior Databricks Data Engineer jobs near you
Infographic showing various Senior Databricks Data Engineer job openings in Torrington, CT as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $124,927 per year, or $60.1 per hour.

DATA Engineer

Teamware Solutions

East Hartford, CT • On-site

$113K - $136K/yr

Other

Posted 9 days ago

Job description

 
 

Must be Local only within 40 Miles area

Relocation will not work

 
 
Look insurance domain highly preferred
 
 

Job Description:

11 Years exp 

We are looking for a Senior Data Engineer to design, build, and optimize scalable data pipelines and warehouse solutions that power business-critical analytics. You will work closely with data architects, analysts, and business stakeholders to deliver robust data products on modern lakehouse platforms.
Key Responsibilities
  • Design and develop end-to-end data pipelines using Apache Spark and Databricks, following medallion (Bronze/Silver/Gold) architecture patterns
  • Build and maintain large-scale SQL-based data warehouses, including dimensional models, star/Client schemas, and performance-tuned queries
  • Lead data ingestion from diverse sources (RDBMS, APIs, flat files, streaming) into centralized platforms with strong data quality controls
  • Implement and enforce Unity Catalog governance standards — data lineage, access controls, tagging, and cataloging
  • Optimize Spark jobs for performance, cost efficiency, and reliability at scale
  • Collaborate with architects to define standards for data modeling, pipeline design, and naming conventions
  • Mentor junior engineers and conduct code reviews to uphold engineering best practices
  • Partner with business analysts and data consumers to translate requirements into scalable data solutions
  • Proactively identify and resolve data quality, latency, and pipeline reliability issues
Required Skills & Qualifications
  • 10+ years of hands-on experience in data engineering
  • Strong expertise in Apache Spark (PySpark / Scala) and Databricks platform
  • Deep proficiency in SQL — query optimization, window functions, complex transformations, stored procedures
  • Solid experience with data warehousing concepts — normalization, SCD types, fact/dimension modeling
  • Experience with Client Lake or similar open table formats (Apache Iceberg, Hudi)
  • Hands-on with orchestration tools such as Apache Airflow, Databricks Workflows, or Azure Data Factory
  • Familiarity with version control (Git) and CI/CD practices for data pipelines
  • Strong understanding of data governance — lineage, cataloging, data quality frameworks
  • Excellent problem-solving skills and ability to work independently in a client-facing environment
Good to Have
  • Experience with dbt (data build tool) for transformation layer development
  • Exposure to cloud platforms — AWS
  • Knowledge of streaming technologies (Kafka, Event Hubs)
  • Familiarity with Great Expectations or other data quality frameworks

Apply