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Databricks Engineer Jobs in Connecticut (NOW HIRING)

Sr Data Engineer

Shelton, CT · On-site

$106K - $144K/yr

Implement Lambda or Kappa architectures using Databricks Structured Streaming / DLT or Snowflake ... Raise engineering maturity by shipping working examples and codifying patterns. * Foster a culture ...

Sr Data Engineer

Shelton, CT · On-site

$106K - $144K/yr

Implement Lambda or Kappa architectures using Databricks Structured Streaming / DLT or Snowflake ... Raise engineering maturity by shipping working examples and codifying patterns. * Foster a culture ...

Sr Data Engineer

Shelton, CT

$106K - $144K/yr

Implement Lambda or Kappa architectures using Databricks Structured Streaming / DLT or Snowflake ... Raise engineering maturity by shipping working examples and codifying patterns. * Foster a culture ...

Sr Data Engineer

Shelton, CT · On-site

$106K - $144K/yr

Implement Lambda or Kappa architectures using Databricks Structured Streaming / DLT or Snowflake ... Raise engineering maturity by shipping working examples and codifying patterns. * Foster a culture ...

Sr Data Engineer

Shelton, CT · On-site

$106K - $144K/yr

Implement Lambda or Kappa architectures using Databricks Structured Streaming / DLT or Snowflake ... Raise engineering maturity by shipping working examples and codifying patterns. * Foster a culture ...

Sr Data Engineer

Shelton, CT

$106K - $144K/yr

Implement Lambda or Kappa architectures using Databricks Structured Streaming / DLT or Snowflake ... Raise engineering maturity by shipping working examples and codifying patterns. * Foster a culture ...

Sr Data Engineer

Shelton, CT · On-site

$106K - $144K/yr

Implement Lambda or Kappa architectures using Databricks Structured Streaming / DLT or Snowflake ... Raise engineering maturity by shipping working examples and codifying patterns. * Foster a culture ...

Sr Data Engineer

Shelton, CT · On-site

$106K - $144K/yr

Implement Lambda or Kappa architectures using Databricks Structured Streaming / DLT or Snowflake ... Raise engineering maturity by shipping working examples and codifying patterns. * Foster a culture ...

Sr Data Engineer

Shelton, CT

$106K - $144K/yr

Implement Lambda or Kappa architectures using Databricks Structured Streaming / DLT or Snowflake ... Raise engineering maturity by shipping working examples and codifying patterns. * Foster a culture ...

Sr Data Engineer

Shelton, CT · On-site

$114K - $137K/yr

Implement Lambda or Kappa architectures using Databricks Structured Streaming / DLT or Snowflake ... Raise engineering maturity by shipping working examples and codifying patterns. * Foster a culture ...

Sr Data Engineer

Shelton, CT

$106K - $144K/yr

Implement Lambda or Kappa architectures using Databricks Structured Streaming / DLT or Snowflake ... Raise engineering maturity by shipping working examples and codifying patterns. * Foster a culture ...

Sr. Data Engineer

Southbury, CT

$105K - $143K/yr

Hands-on experience building lakehouse solutions on Databricks (Delta Lake, Unity Catalog) or ... Programming: Strong PySpark or advanced SQL skills; Python for data engineering or automation.

New

Sr. Data Engineer

Shelton, CT · On-site

$106K - $144K/yr

Hands-on experience building lakehouse solutions on Databricks (Delta Lake, Unity Catalog) or ... Programming: Strong PySpark or advanced SQL skills; Python for data engineering or automation.

Sr. Data Engineer

Shelton, CT

$106K - $144K/yr

Hands-on experience building lakehouse solutions on Databricks (Delta Lake, Unity Catalog) or ... Programming: Strong PySpark or advanced SQL skills; Python for data engineering or automation.

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Showing results 1-20

Databricks Engineer information

See Connecticut salary details

$56.6K

$106.2K

$193.1K

How much do databricks engineer jobs pay per year?

As of Jul 15, 2026, the average yearly pay for databricks engineer in Connecticut is $106,194.00, according to ZipRecruiter salary data. Most workers in this role earn between $76,600.00 and $126,000.00 per year, depending on experience, location, and employer.

What engineer makes $500,000 a year?

Senior Databricks Engineers with extensive experience, specialized skills in big data, cloud platforms, and advanced analytics can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or with significant bonuses and stock options. Such compensation typically requires a combination of technical expertise, leadership roles, and years of industry experience.

Is Databricks Data Engineer in demand?

Databricks Data Engineers are in high demand due to the increasing adoption of cloud-based data platforms and the need for expertise in big data processing, Spark, and cloud environments. Companies seek professionals skilled in data pipeline development, ETL processes, and cloud tools like AWS or Azure, making this a strong job market for qualified candidates.

What are some common challenges faced by Databricks Engineers when working with large-scale data pipelines?

Databricks Engineers often encounter challenges related to optimizing the performance and reliability of large-scale data pipelines. These can include efficiently managing cluster resources, handling data partitioning to prevent bottlenecks, and troubleshooting job failures due to resource constraints or data quality issues. Collaboration with data scientists, analysts, and DevOps teams is essential to ensure seamless integration and deployment of production workflows. Staying current with evolving Databricks features and best practices also plays a key role in overcoming these challenges.

How much does a Databricks engineer make?

A Databricks engineer's salary typically ranges from $100,000 to $150,000 annually, depending on experience, location, and skill level. Senior roles or those with specialized skills in Spark, cloud platforms, or data engineering may earn higher compensation. Salaries can also vary based on industry demand and certifications held.

Is Databricks a high paying job?

A Databricks Engineer typically earns a high salary due to the specialized skills required in cloud computing, big data processing, and Spark platform expertise. Compensation varies based on experience, location, and certifications, but it is generally above average for data engineering roles.

What is a Databricks Engineer?

A Databricks Engineer is a data engineering professional who specializes in using the Databricks platform to build, manage, and optimize data pipelines and analytics solutions. They work with big data technologies like Apache Spark, Delta Lake, and cloud services to process and analyze large datasets efficiently. Their role often involves developing ETL (extract, transform, load) workflows, setting up data lakes, and ensuring data quality and performance for business intelligence and machine learning applications.

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

To thrive as a Databricks Engineer, you need strong expertise in big data processing, cloud platforms (like AWS or Azure), and proficiency with languages such as Python, SQL, and Scala, often supported by a degree in computer science or a related field. Familiarity with Apache Spark, Databricks Workspace, version control systems like Git, and relevant Databricks certifications are typically required. Strong analytical thinking, collaboration, and effective communication skills help you understand business needs and work seamlessly with data teams. These skills ensure efficient data pipeline development, scalable analytics solutions, and successful integration of Databricks into organizational workflows.
What are popular job titles related to Databricks Engineer jobs in Connecticut? For Databricks Engineer jobs in Connecticut, the most frequently searched job titles are:
What job categories do people searching Databricks Engineer jobs in Connecticut look for? The top searched job categories for Databricks Engineer jobs in Connecticut are:
What cities in Connecticut are hiring for Databricks Engineer jobs? Cities in Connecticut with the most Databricks Engineer job openings:
Sr Data Engineer

Sr Data Engineer

subway

Shelton, CT • On-site

$106K - $144K/yr

Other

Medical, Life, Retirement

Posted 16 days ago


Subway rating

4.4

Company rating: 4.4 out of 10

Based on 2,028 frontline employees who took The Breakroom Quiz

97th of 104 rated fast food restaurants


Job description

 

Sr Data Engineer - Shelton, CT

Ready to build what’s next with one of the world’s most iconic brands? 

Why Join Subway? 

At Subway, we are not standing still. We are building. 

This is a business focused on what matters most: growing franchisee profitability, strengthening our brand and creating long-term value. The people who thrive here are the ones who want to make a real impact. 

You will not just do the work. You will shape it. 

We move fast. We think like owners. We make decisions that matter. We hold ourselves to a high standard because what we do directly impacts thousands of franchisees around the world. 

If you bring energy, accountability and a bias for action, you will fit right in. 

We take the work seriously, but we also know the best results come from teams that support each other, celebrate wins and show up ready to build something better every day. 

This is your chance to be part of what’s next. 

About the Role: 

The Sr Data Engineer is a senior-level, hands-on technical leader responsible for designing, building, and evolving Subway’s enterprise data platform on Snowflake or Databricks. This role serves as a technical authority and builder, driving Lakehouse architecture, engineering frameworks, and best practices across multiple data domains. The Sr Data Engineer operates with a high degree of autonomy, leading through working code and influence — shipping reference implementations, POCs, and platform-level solutions that other teams build upon. 

Responsibilities include but not limited to: 

  • Personally design and build reference implementations and production-grade frameworks on Databricks or Snowflake.
  • Design lakehouse platforms using Delta Lake or Iceberg Tables with Medallion (Bronze/Silver/Gold) architecture.
  • Define and evolve enterprise data standards, patterns, and reusable accelerators.
  • Ensure solutions align with data governance, security, scalability, and cost-efficiency standards.
  • Evaluate technologies through hands-on benchmarking — not vendor decks.
  • Build the first working version of complex pipelines, frameworks, and POCs (ingestion, CDC, streaming, DQ, observability, CI/CD).
  • Drive emerging tech (Iceberg, Lakeflow, Openflow, Cortex, Mosaic AI) from POC to production rollout.
  • Solve high-complexity performance, cost, and governance challenges at petabyte scale.
  • Identify and address systemic technical debt and architectural risks.
  • Implement Lambda or Kappa architectures using Databricks Structured Streaming / DLT or Snowflake Dynamic Tables / Snowpipe Streaming.
  • Build GenAI and ML enablement patterns (RAG, feature stores, semantic layers) using Databricks Mosaic AI or Snowflake Cortex.
  • Partner with Data Science and Analytics teams to operationalize models and AI workflows.
  • Collaborate closely with Product, Architecture, Security, Infrastructure, and Analytics leaders.
  • Translate business needs into sound technical direction backed by working prototypes.
  • Communicate technical trade-offs, risks, and decisions clearly to technical and non-technical stakeholders.
  • Influence roadmaps and platform investments through technical insight and de-risking POCs.
  • Mentor Senior and Staff Data Engineers through pair-programming, PR reviews, and design coaching.
  • Raise engineering maturity by shipping working examples and codifying patterns.
  • Foster a culture of technical excellence, learning, and continuous improvement. 

Qualifications (some examples listed below): 

  • Exceptional hands-on expertise in Databricks or Snowflake lakehouse platforms.
  • Deep proficiency in PySpark or advanced SQL, plus Python for data engineering and automation.
  • Proven experience building Medallion architecture with Delta Lake or Iceberg Tables. 
  • Real-time and batch streaming experience (Lambda or Kappa) using Databricks DLT or Snowflake Dynamic Tables / Snowpipe Streaming. 
  • Hands-on with orchestration tools — Airflow, Databricks Lakeflow, or Snowflake Openflow; dbt experience a plus.
  • Strong data modeling skills (Dimensional, Data Vault, schema design).
  • Performance and cost tuning expertise (clustering, partitioning, Z-ordering, warehouse/cluster sizing, FinOps). 
  • Governance experience with Unity Catalog (Databricks) or Horizon Catalog (Snowflake) for lineage, access control, and data quality.
  • Semantic layer experience using Databricks AI/BI Genie / Unity Catalog Metrics or Snowflake Semantic Views / Cortex Analyst.
  • AI/ML enablement experience with Databricks Mosaic AI or Snowflake Cortex.
  • CI/CD and DevOps fluency — Git, Databricks Asset Bundles or Snowflake CLI / Schemachange, automated testing.
  • Cloud ecosystem expertise — AWS (S3, Glue, Kinesis), Azure, or GCP.
  • Excellent communication and technical storytelling ability.
  • Comfortable operating across ambiguity and complex stakeholder environments. 
  • Education: Bachelor’s degree required (Computer Science, Engineering, or related field); advanced degree preferred.
  • Experience: 3-5 years of professional data engineering experience, with proven track record leading architecture and hands-on build for enterprise-scale data platforms, operating in complex or mission-critical data environments, and influencing multiple teams and platforms without direct authority.
  • Travel Requirements: Minimal to moderate (up to 10%, as business needs require). 

What do we offer? 

  • Insurance Plans (Medical, Life)
  • Pension/401K/RSP (country specific)
  • Competitive Bonus
  • Mobility Allowance
  • Tuition Reimbursement
  • Company Holidays
  • Volunteering time
  • And More….. 

 

Compensation: The base pay range for this role is $102,700 - $128,400 annually

Pay within this range will be determined in good faith based on job-related factors, which may include skills, experience, education/training, location, and internal equity.


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