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Data Engineer Data Bricks Jobs (NOW HIRING)

Apex Informatics

Data Engineer

$117K - $140K/yr

Position: Data Engineer Location: Remote Duration: 9 Months (Contract) • Gather business ... Data bricks • Participate in ETL QA • Participate on deployment process using CICD • ...

Noblesoft Technologies

Data Engineer

Princeton, NJ · On-site

$120K - $144K/yr

Data Engineer location : Princeton, NJ Minimum Mandatory Skills ... ADF, Data Bricks Desired Skills: Python, PySpark Key Responsibilities: * Design and implement ETL ...

Mindlance

Data Engineer

Minneapolis, MN · On-site

$119K - $143K/yr

Data Bricks and/or Snowflake Skills: ETL Yes 1 2 - 4 Years SSIS Yes 1 2 - 4 Years Advanced SQL query writing Yes 1 2 - 4 Years Data Engineer Yes 1 1 - 2 Years Data Management Yes 1 1 - 2 Years ...

New

Vergence

ETL/Data Engineer

Indianapolis, IN · On-site

$107K - $129K/yr

... Data Bricks and/or Microsoft Fabric Data Factory. • Implement medallion architecture (Bronze ... Platform Engineering & DevOps • Implement CI/CD for data pipelines using Azure DevOps (YAML ...

Vergence

ETL/Data Engineer

Indianapolis, IN

$107K - $129K/yr

... Data Bricks and/or Microsoft Fabric Data Factory. • Implement medallion architecture (Bronze ... Platform Engineering & DevOps • Implement CI/CD for data pipelines using Azure DevOps (YAML ...

DATAMAXIS

Senior Azure Data Engineer

Springfield, IL

$113K - $136K/yr

... Data Bricks and/or Microsoft Fabric Data Factory. * Implement medallion architecture (Bronze ... Platform Engineering & DevOps * Implement CI/CD for data pipelines using Azure DevOps (YAML ...

ACI Infotech

Senior Data Engineer

Charlotte, NC · On-site

$103K - $140K/yr

Azure Data bricks (ADF) * Power BI Experience or BI tool experience * Optimize data storage and access strategies for performance and cost-efficiency. * Ensure data quality, integrity, and security ...

ARMADA

Data Engineer

Wexford, PA · On-site

$108K - $130K/yr

SUMMARY As a Data Engineer for our Digital Services division, you will drive the evolution of our ... Data Bricks, etc. * Solid understanding of machine learning models, tools, libraries, and ...

Zortech Solutions

Azure Data Engineer

Iselin, NJ · On-site

$116K - $139K/yr

Snowflake SQL Python ADF Azure Data Bricks PySpark Data Warehouse Concepts : This position is for a Cloud Data engineer with a background in Python, Pyspark, SQL and data warehousing for enterprise ...

Tror AI for everyone

Data Engineer

New York, NY · On-site

$125K - $150K/yr

Redshift or Snowflake or Big Query Data Integration & ETL: AWS Glue, Aws EMR, Spark, Data Bricks CI/CD: AWS Code Pipeline, Jenkins, CloudFormation, Docker, Kubernetes * Results-driven Data Engineer ...

Net Orbit

Azure Data Engineer

Houston, TX · On-site

$105K - $126K/yr

Azure Data Engineer Houston TX - Onsite from day 1 Project Overview: New project- credit card ... Data Lake, Data Bricks, Tableau * Arch level convos * Can interface with other partners onsite ( ex.

STEMtech

Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

Hadoop, Map/Reduce, Spark, HBase, HDInsight, Data Bricks, Hive) and with programming languages like UNIX shell scripting, Python etc. Has used SQL, PL/SQL or T-SQL with RDBMSs like Teradata, MS SQL ...

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How much do data engineer data bricks jobs pay per year?

As of Jul 14, 2026, the average yearly pay for data engineer data bricks in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

What are Data Engineer Data Bricks?

A Data Engineer specializing in Databricks is a professional who designs, builds, and maintains data pipelines and infrastructure using the Databricks platform. Databricks is a cloud-based data analytics platform that facilitates big data processing, machine learning, and collaborative analytics. Data Engineers use Databricks to process large datasets, automate data workflows, and support data-driven decision-making for organizations. Their responsibilities often include cleaning and transforming data, optimizing data storage, and ensuring efficient data movement across systems.

What is the difference between Data Engineer Data Bricks vs Data Engineer Apache Spark?

AspectData Engineer Data BricksData Engineer Apache Spark
CredentialsTypically requires cloud platform certifications (Azure, AWS), Spark knowledge, and data engineering skillsRequires Spark expertise, programming skills, and often similar cloud certifications
Work EnvironmentCloud-based platforms with integrated tools, collaborative environment, managed servicesOn-premises or cloud, more manual setup, flexible environment
Industry UsagePopular in cloud-centric companies, data lakes, and analytics platformsWidely used across industries for big data processing, on-premises or cloud

Data Engineer Data Bricks focuses on cloud-based, managed Spark environments with integrated tools, while Data Engineer Apache Spark emphasizes core Spark skills applicable in various environments. Both roles require similar technical knowledge but differ mainly in platform and deployment context.

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

To thrive as a Data Engineer specializing in Databricks, you need strong expertise in data modeling, ETL processes, and proficiency with programming languages such as Python or Scala, often supported by a degree in computer science or a related field. Familiarity with Databricks, Apache Spark, SQL, cloud platforms (like AWS or Azure), and relevant certifications (such as Databricks Certified Data Engineer) is typically required. Strong analytical thinking, problem-solving, and effective communication are crucial soft skills for collaborating with cross-functional teams and translating business needs into data solutions. These skills ensure efficient data pipeline development, reliable data management, and impactful analytics in data-driven organizations.

What are some common challenges Data Engineers face when working with Databricks, and how can they be addressed?

Data Engineers working with Databricks often encounter challenges related to optimizing large-scale data pipelines, managing cluster resources efficiently, and ensuring seamless data integration across varied sources. Addressing these issues typically involves staying current with Databricks best practices, such as implementing Delta Lake for reliable data storage, using job scheduling to automate workflows, and proactively monitoring cluster performance. Collaborating closely with data scientists and analysts is also crucial to align data models and streamline the analytics process.
More about Data Engineer Data Bricks jobs
What cities are hiring for Data Engineer Data Bricks jobs? Cities with the most Data Engineer Data Bricks job openings:
What states have the most Data Engineer Data Bricks jobs? States with the most job openings for Data Engineer Data Bricks jobs include:
What job categories do people searching Data Engineer Data Bricks jobs look for? The top searched job categories for Data Engineer Data Bricks jobs are:
Data Engineer Data Bricks jobs near you
Infographic showing various Data Engineer Data Bricks job openings in the United States as of July 2026, with employment types broken down into 2% Locum Tenens, 35% Internship, 2% As Needed, 48% Full Time, 12% Part Time, and 1% Summer. Highlights an 99% Physical, and 1% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.
Data Bricks Migration and Support engineer

Data Bricks Migration and Support engineer

Tata Consultancy Services

Seattle, WA • On-site

$130K - $156K/yr

Full-time

Re-posted 7 days ago

Tata Consultancy Services rating

6.5

Company rating: 6.5 out of 10

Based on 21 frontline employees who took The Breakroom Quiz

159th of 210 rated it services

Job description

Job Summary:
Tata Consultancy Services is seeking a Data Bricks Migration and Support Engineer to lead and manage large data migrations to Data Bricks, specifically from IBM DataStage. The role involves executing data migration projects, ensuring data governance, and optimizing performance while supporting the post-migration environment.
Responsibilities:
• Support post-migration environment from IBM DataStage to Databricks
• CI/CD Deployment: Support code deployments across Development, Test, and Production environments using Databricks Repos and REST APIs
• Monitoring & Alerting: Set up monitoring via Databricks System Tables and observability tools to catch job failures, data anomalies, or latency spikes early
• Workflow Management: Transition from DataStage job sequences to native data bricks workflows for scheduling, dependency tracking, and alerts
• ETL Refactoring: Troubleshoot and fix issues in generated PySpark or Spark SQL code that replaced legacy DataStage Transformer or Lookup stages
• Streaming & Batch Integration: Support ongoing data ingestion using data bricks autoloader to process files continuously from cloud storage
• Compute Management: Monitor and configure serverless or classic clusters to prevent over-provisioning
• Query Optimization: Analyze Spark execution plans. Replace inefficient row-by-row processing logic (a common DataStage carryover) with vectorized operations and native Spark functions
• Storage Optimization: Maintain Delta Lake tables by enforcing layout optimization (ZORDER)
• Access Control: Implement granular permissions, column-masking, and row-level filters using Data bricks unity catalog to replace DataStage's legacy security policies
• Data Quality: Utilize Delta Live Tables (DLT) to build pipelines with built-in, declarative data quality expectations and monitoring
Qualifications:
Required:
• Successfully executed a data migration or modernization to Data Bricks, preferably IBM Data Stage to Data Bricks on AWS
• Experience in handling Large Migrations to Data Bricks
• Good analytical skills to compare the legacy and modern data platform end to end right from source to target
• Good understanding of DataBricks implementation of Medallion layer architecture
• Independently Lead and Managed large Data Bricks migrations
• CI/CD Integration: Implement version control (e.g., Git) and automated deployment processes for Databricks assets
• Experience in Advanced SQL for building modular analytics workflows, utilizing advanced Common Table Expressions (CTEs), and writing high-performance queries inside Data Bricks SQL Analytics
• Experience in Python or Scala to build, optimize, and debug complex data transformation scripts, custom functions, and machine learning pipelines
• Experience in Apache Spark Ecosystem for understanding cluster execution flow, memory allocation, driver/worker nodes, and handling data frames
• Experience in Delta Lake Architecture to understand ACID transactions on object storage, data skipping, partition strategies, and automated data compaction
• Experience in Delta Live Tables (DLT) & Workflows for constructing and orchestrating production-ready, declarative streaming, and batch ETL pipelines
• Experience in Unity Catalog for setting up data governance, column/row-level access control, and tracking end-to-end data lineage across workspaces
• Experience in Auto Loader for implementing modern, incremental data ingestion patterns from cloud blob storage into the lakehouse
• Pipeline Conversion: Translate visual DataStage Parallel Jobs and Sequences into Python/PySpark scripts or Data bricks Notebooks
• Legacy Refactoring: Modernize legacy logic rather than applying 'lift and shift' anti-patterns; adapt workflows to think in distributed DataFrames rather than DataStage stages
• Logic Mapping: Map DataStage components—such as Aggregators, Joiners, Transformers, and Sort stages—to equivalent Spark operations
• Validation & Reconciliation: Build automated reconciliation frameworks to compare row counts, checksums, and aggregate sums between legacy DataStage outputs and new Databricks output
• Data Cleansing: Identify and resolve data type discrepancies, null-handling differences, and encoding issues during the extraction and loading phases
• Orchestration: Replace DataStage sequence jobs with Databricks workflows (or external orchestrators like Azure Data Factory/Airflow) to schedule and manage dependencies
• Data Governance: Enforce data lineage, security, and cataloging using Unity Catalog to ensure compliance in the new Lakehouse environment
• Cloud Providers (AWS): Understanding underlying cloud object storage, identity access management (IAM), and network security configurations
• Familiarity with Databricks Asset Bundles (DABs) and CI/CD tools to automate the deployment of workspaces and pipeline assets
• The ability to parse legacy code structures and refactor them into Databricks-native code
• Skills in using AI coding assistants and open framework agent tools to analyze application interdependencies, automate schema mapping, and accelerate lift-and-shift workloads
• Experience working in Agile teams and understanding of data governance frameworks
• Support post-migration environment from IBM DataStage to Databricks
• CI/CD Deployment: Support code deployments across Development, Test, and Production environments using Databricks Repos and REST APIs
• Set up monitoring via Databricks System Tables and observability tools to catch job failures, data anomalies, or latency spikes early
• Transition from DataStage job sequences to native data bricks workflows for scheduling, dependency tracking, and alerts
• Troubleshoot and fix issues in generated PySpark or Spark SQL code that replaced legacy DataStage Transformer or Lookup stages
• Support ongoing data ingestion using data bricks autoloader to process files continuously from cloud storage
• Monitor and configure serverless or classic clusters to prevent over-provisioning
• Analyze Spark execution plans. Replace inefficient row-by-row processing logic (a common DataStage carryover) with vectorized operations and native Spark functions
• Maintain Delta Lake tables by enforcing layout optimization (ZORDER)
• Implement granular permissions, column-masking, and row-level filters using Data bricks unity catalog to replace DataStage's legacy security policies
• Utilize Delta Live Tables (DLT) to build pipelines with built-in, declarative data quality expectations and monitoring
• Excellent communication Skills
• Ability to collaborate with Legacy and Modernize application teams and stakeholders
• BACHELOR OF COMPUTER SCIENCE
Company:
Tata Consultancy Services is a business solutions company that specializes on information technology services and consulting. It is a sub-organization of Tata Group. Founded in 1968, the company is headquartered in Mumbai, IND, with a team of 10001+ employees. The company is currently Late Stage.

What Tata Consultancy Services employees say

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About Tata Consultancy Services

Sourced by ZipRecruiter

Tata Consultancy Services is an IT services, consulting and business solutions organization that delivers real results to global business, ensuring a level of certainty no other firm can match. TCS offers a consulting-led, integrated portfolio of IT, BPO, infrastructure, engineering, and assurance services. This is delivered through its unique Global Network Delivery Model™, recognized as the benchmark of excellence in software development. TCS delivers a level of certainty that no other firm can match--to our clients and to our employees. Come join us and experience certainty in your career. TCS a global Consulting and IT Services firm that is ranked in the top quartile by industry analysts. Our 2021 fiscal revenues topped $25 B and our market capitalization is over $170+B, yet we have a deep and large history of philanthropy and corporate social responsibility. Now approaching 600K of the best IT professionals and consultants, we are a trusted advisor, guiding our clients' enterprises through growth and transformation journeys - helping them to become agile, intelligent, automated and on the cloud. We are devoted to DEI and are recognized as a top employer and place to work.

Industry

It services

Company size

10,000+ Employees

Headquarters location

Edison, NJ, US

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