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Databricks Architect Jobs in Connecticut (NOW HIRING)

Sr. Data Engineer

Shelton, CT · On-site

$106K - $144K/yr

Lakehouse Architecture: Hands-on experience building lakehouse solutions on Databricks (Delta Lake, Unity Catalog) or Snowflake (Iceberg Tables, Horizon Catalog). * Medallion Architecture: Proven ...

Sr. Data Engineer

Shelton, CT · On-site

$106K - $144K/yr

Lakehouse Architecture: Hands-on experience building lakehouse solutions on Databricks (Delta Lake, Unity Catalog) or Snowflake (Iceberg Tables, Horizon Catalog). * Medallion Architecture: Proven ...

Sr. Data Engineer

Shelton, CT · On-site

$106K - $144K/yr

Lakehouse Architecture: Hands-on experience building lakehouse solutions on Databricks (Delta Lake, Unity Catalog) or Snowflake (Iceberg Tables, Horizon Catalog). * Medallion Architecture: Proven ...

Sr. Data Engineer

Shelton, CT · On-site

$106K - $144K/yr

Lakehouse Architecture: Hands-on experience building lakehouse solutions on Databricks (Delta Lake, Unity Catalog) or Snowflake (Iceberg Tables, Horizon Catalog). * Medallion Architecture: Proven ...

Senior Data Engineer

Hartford, CT · Hybrid

$106K - $145K/yr

Design, develop and optimize ETL/ELT pipelines using Azure Data Factory (ADF) and Databricks * Write and tune PySpark / Spark SQL notebooks for large-scale data transformation * Architect end-to-end ...

Senior Data Engineer

Stamford, CT · Hybrid

$113K - $153K/yr

Design, develop and optimize ETL/ELT pipelines using Azure Data Factory (ADF) and Databricks * Write and tune PySpark / Spark SQL notebooks for large-scale data transformation * Architect end-to-end ...

... Architect, Azure Data Engineer Associate, or Snowflake Core, Snowflake Databricks Data Engineer Associate] is a plus - Designing and implementing thorough data architecture strategies that meet the ...

... Architect, Azure Data Engineer Associate, or Snowflake Core, Snowflake Databricks Data Engineer Associate] is a plus - Designing and implementing thorough data architecture strategies that meet the ...

... Architect, Databricks Data Engineer Associate] is a plus - Designing and implementing thorough data architecture strategies - Developing and documenting data models and data flow diagrams ...

... Architect, Databricks Data Engineer Associate] is a plus - Designing and implementing thorough data architecture strategies - Developing and documenting data models and data flow diagrams ...

Your work will span across systems architecture, network systems, and application infrastructure to ... Snowflake, Databricks/Unity Catalog, Tableau/Power BI scanners and lineage connectors. OTHER JOB ...

... Solutions Architect, Azure Data Engineer Associate, Snowflake Core, Snowflake Databricks Data Engineer Associate] is a plus - Designing and implementing thorough data architecture strategies ...

... Solutions Architect, Azure Data Engineer Associate, Snowflake Core, Snowflake Databricks Data Engineer Associate] is a plus - Designing and implementing thorough data architecture strategies ...

Showing results 41-60

Databricks Architect information

What is a Databricks Architect?

A Databricks Architect is an IT professional who designs, implements, and manages data solutions using the Databricks platform, which is built on Apache Spark. They are responsible for creating scalable data pipelines, optimizing data workflows, and ensuring security and compliance within the cloud environment. Databricks Architects often work closely with data engineers, data scientists, and business stakeholders to deliver robust analytics solutions that drive business insights. Their expertise helps organizations leverage big data technologies efficiently and effectively.

What are the key skills and qualifications needed to thrive as a Databricks Architect?

To thrive as a Databricks Architect, you need strong expertise in big data engineering, cloud platforms (such as Azure or AWS), distributed computing, and proficiency in languages like Python or Scala, typically supported by a relevant degree and cloud certifications. Familiarity with Databricks Workspace, Apache Spark, Delta Lake, and CI/CD tools is crucial for designing and implementing scalable data solutions. Excellent problem-solving, communication, and project management skills set top performers apart by enabling effective collaboration and solution delivery. These competencies are essential for architecting reliable, high-performance data platforms that drive business insights and innovation.

What are some common challenges Databricks Architects face when designing large-scale data solutions?

Databricks Architects often encounter challenges such as optimizing cluster performance for cost and efficiency, ensuring data security and compliance across distributed environments, and integrating Databricks with legacy systems or diverse data sources. They must carefully design data pipelines and workflows to handle large volumes of data without bottlenecks, and also collaborate closely with data engineers, data scientists, and IT teams to align on best practices. Staying updated with evolving Databricks features and cloud platform updates is also essential for success in this dynamic role.

What is the difference between Databricks Architect vs Data Engineer?

AspectDatabricks ArchitectData Engineer
Primary FocusDesigning and implementing data solutions on Databricks platformBuilding, maintaining, and optimizing data pipelines and infrastructure
Skills & CertificationsDatabricks certifications, Spark, cloud platforms (AWS, Azure), SQLSQL, ETL tools, cloud platforms, programming (Python, Scala)
Work EnvironmentData platforms, cloud environments, collaboration with data teamsData pipelines, databases, cloud infrastructure, scripting

While both roles work with data and cloud platforms, a Databricks Architect primarily focuses on designing and implementing data solutions using Databricks, whereas a Data Engineer builds and maintains the data pipelines and infrastructure that support these solutions. The Architect often oversees the technical design, while the Engineer handles the day-to-day pipeline development.

What are the most commonly searched types of Databricks Architect jobs in Connecticut?

The most popular types of Databricks Architect jobs in Connecticut are:

What are popular job titles related to Databricks Architect jobs in Connecticut?

For Databricks Architect jobs in Connecticut, the most frequently searched job titles are:

Infographic showing various Databricks Architect job openings in Connecticut as of August 2026, with employment types broken down into 89% Full Time, 4% Part Time, and 7% Contract. Highlights an 76% Physical, 7% Hybrid, and 17% Remote job distribution.

Sr. Data Engineer

subway

Shelton, CT • On-site

$106K - $144K/yr

Full-time

Medical, Life, Retirement

Re-posted 19 days ago


Subway rating

4.4

Company rating: 4.4 out of 10

Based on 2,053 frontline employees who took The Breakroom Quiz

98th of 106 rated fast food restaurants


Job description

Senior Data Engineer

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 will be responsible for the design and development of data pipelines to support System Integrations as well as data pipelines that power our Analytical Platforms. In collaboration with Product Owners and other technical teams, the Sr. Data Engineer will lead significant enterprise-wide work as part of larger cross-functional teams supporting multiple major project initiatives. A candidate will deliver scalable, flexible, and high-quality solutions that conform to Subway’s data design and governance strategies, leveraging our cloud data platform built on Snowflake or Databricks along with other modern cloud-based technologies.

Responsibilities include but not limited to:

  • Design and develop data pipelines and integrations that are performant, scalable and flexible.
  • Work with project teams to deliver system integration pipelines, ensuring a high degree of reliability and resiliency.
  • Work with business users and project teams to provide SME guidance, finalize pipeline requirements and develop level of effort estimates.
  • Develop automated testing and deployment scripts to support integrations and pipelines.
  • Provide database support by coding utilities, responding to user questions, and resolving problems.
  • Create and maintain documentation of data pipelines including data flow and data lineage documentation.
  • Responsible for tier 3 support and assisting our Operations Team as required to provide a great customer experience for our users.
  • Responsible for overall data quality as it relates to our Enterprise Data Warehouse and associated Data Marts. Provide data analysis as required to troubleshoot data issues.
  • Assist with integration related code reviews and mentorship of junior developers.
  • Implement data governance and master data management principles as part of data pipeline development and delivery.

Qualifications (some examples listed below):

  • Lakehouse Architecture: Hands-on experience building lakehouse solutions on Databricks (Delta Lake, Unity Catalog) or Snowflake (Iceberg Tables, Horizon Catalog).
  • Medallion Architecture: Proven ability to design Bronze/Silver/Gold layers for curated, analytics-ready data.
  • Streaming or Batch Processing: Experience implementing Lambda or Kappa architectures using Databricks Structured Streaming / DLT or Snowflake Dynamic Tables / Snowpipe Streaming.
  • Semantic Layer: Experience building and managing semantic models using Databricks AI/BI Genie or Unity Catalog Metrics or Snowflake Semantic Views / Cortex Analyst to enable consistent, governed metrics for BI and AI consumption.
  • ETL/ELT Orchestration: Building pipelines with Airflow, Databricks Lakeflow, or Snowflake Openflow; familiarity with dbt is a plus.
  • Programming: Strong PySpark or advanced SQL skills; Python for data engineering or automation.
  • Data Modeling: Dimensional modeling, Data Vault, or schema design for analytical workloads.
  • Performance Tuning: Cluster/warehouse sizing, partitioning, clustering keys, Z-ordering, or query optimization.
  • Governance & Security: Working knowledge of Unity Catalog (Databricks) or Horizon Catalog (Snowflake) for lineage, access control, or data quality.
  • CI/CD & DevOps: Git, Databricks Asset Bundles or Snowflake CLI/Schemachange, automated testing, or deployment pipelines.
  • Cloud Ecosystem: AWS (S3, Glue, Kinesis), Azure, or GCP services supporting modern data platforms.
  • AI/ML Enablement: Familiarity with Databricks Mosaic AI or Snowflake Cortex for GenAI or ML use cases.
  • Collaboration: Strong communication skills to partner with Product Owners, Analysts, or cross-functional engineering teams.
  • Education: Bachelor’s degree in Computer or Information Science or related field, or equivalent combination of education and experience.
  • Experience: 5–8 years creating quality data pipelines and system integrations with at least 3 years of experience in a cloud environment.

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 $119,200 - 149,000 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.


What Subway employees say

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