1 to 25 of 418 Permanent Databricks Jobs

Job Title: Software Engineer - Principal (Databricks Engineer) Location: Dulles, VA Clearance: Secret (must be able to obtain TS/SCI) Company: Quantum Science Solutions (QSS) Compensation: Open Rate Position Overview Quantum Science Solutions (QSS) is seeking an experienced Senior Software Engineer (Databricks Engineer) to join a highly visible federal cybersecurity contract in Dulles, VA. This role will play a mission … and modernization of legacy cybersecurity systems, as well as the design and deployment of new enterprise security services. The engineer will support teams migrating services, applications, and platforms to Databricks, while optimizing data pipelines, governance, performance, and automation strategies. The ideal candidate will bring deep expertise in cloud-based data engineering, Databricks administration, pipeline orchestration, and secure software development practices … Support teams migrating services, applications, and platforms from legacy back-endsystems to Databricks. •Identify optimal migration paths, build migration plans, and execute delivery. •Migrate data pipelines from NiFi to Databricks, including validation. •Implement the medallion model for data assets on Databricks. •Develop SOPs for integrating data assets into Databricks with a focus on efficiency,instrumentation, and performance. •Optimize development, testing More ❯

Principal Specialist Solutions Architect London, United Kingdom FEQ326R502 While candidates in the listed location(s) are encouraged for this role, candidates in other locations will be considered. At Databricks, we are passionate about enabling data teams to solve the world's toughest problems. Our customers leverage the Databricks Data Intelligence Platform to power their mission critical Data and AI applications … to improve how their organisations leverage data and insights to make better decisions, faster. Customers rely on Databricks for the full range of data workloads, including data engineering, ETL, near real-time streaming, machine learning, SQL analytics, and advanced analytics. As a Product Specialist - Lakebase you will be a deep technical expert in OLTP systems and in how customers can … a reality for our customers. You will provide thought leadership on best practices around how to build and deploy Lakebase applications with Databricks. You will work closely with the Databricks Product Management team to drive adoption of Lakebase and ensure a consistent product vision for the EMEA technical field. You will work closely with Sales and FE leaders to help More ❯

Delivery Solutions Architect (Data & AI, Project Delivery) London, United Kingdom CSQ426R275 At Databricks, we are on a mission to empower our customers to solve the world's toughest data problems by utilizing the the Databricks Data Intelligence Platform. As a Delivery Solutions Architect (DSA), you will play an important role during this journey. You will collaborate with our sales and … field engineering teams to accelerate the adoption and growth of the Databricks platform in your customers. You will also help ensure customer success by increasing focus and technical accountability to our most complex customers who need guidance to accelerate usage on Databricks workloads that they have already selected, helping them maximise the value they get of our platform and the … sense that you will drive growth in your assigned customers and use cases through leading your customers' stakeholders, building executive relationships, orchestration of other focused/specialized teams within Databricks, and creating and driving plans and strategies for Databricks colleagues to build upon. This is in parallel to being technical, with expectations being that you become the post-sale technical More ❯

large-scale data systems Expertise in cloud-based data platforms (AWS, Azure, Google Cloud) and distributed storage solutions Proficiency in Python, PySpark, SQL, NoSQL, and data processing frameworks (Spark, Databricks) Expertise in ETL/ELT design and orchestration in Azure, as well as pipeline performance tuning & optimisation Competent in integrating relational, NoSQL, and streaming data sources Management of CI/ More ❯

testing methodologies and development team collaboration Experience working with Power BI and DAX Strong documentation, communication, and stakeholder engagement skills Preferred Qualifications: Experience with Lakehouse architecture, Delta Lake, or Databricks Exposure to Agile/Scrum working practices Microsoft certifications (e.g., Azure Data Engineer Associate) Background in consulting or professional services Understanding of data governance and data security principles Nice to More ❯

existing code, process improvement recommendation, and automation of operations and maintenance tasks Expertise in architect and utilization of large-scale data processing, computationally intensive statistical modeling, and advanced analytics Databricks and Lakehouse architectures AWS OpenSearch Experience with AWS, Splunk, Databricks, and other Oracle/SQL based platforms. Experience with python, Microsoft VBA, and Databricks Databricks Alteryx Designer Cloud (previously Trifacta … Microsoft PowerBI Apache Niagra Files (NiFi) Apache TIKA Databricks and Lakehouse architecture ElasticSearch AWS SQS ElasticSearch and OpenSearch .NET, C#, Javascript, and Java Terraform Experience developing and maintaining components in AWS SpringBoot framework Experience with ELK stack, OpenSearch, SonarQube, Cypress, PowerShell, C#, and Databricks Experience with Docker, SQL, Angular, Spring Boot, Nifi, AWS, python, scala, shell scripting, and XML processing … Experience in AWS solution architecture Experience in ElasticSearch, Vue.js, Java Spring Framework, and .NET Framework web services. Vue3, Typescript, Jupyter Notebook, Scala, Databricks Node.js, Angular JS, HTML, CSS, Java Script, Bootstrap, d3, AJAX, Visual Studio, other skills include RubyGems, Python, Redhat Linux Experience supporting users in bulk data processing with machine translation, speech to text and OCR tools to include More ❯

candidate. If you meet around 75% of the criteria, we'd still love to hear from you. • Strong experience with data engineering tools and platforms (e.g. Azure Data Factory, Databricks, SQL, Python). • Proven ability to engage stakeholders and present insights through data visualisation tools and storytelling. • Experience with data modelling, warehousing, and integration. • Interest in and awareness of AI More ❯

can influence promised outcomes. Drive high client value and broaden relationships at senior levels with current and prospective clients. Our Tech Stack Cloud: Azure, sometimes GCP & AWS Data Platform: Databricks, Snowflake, BigQuery Data Engineering tools: Pyspark, Polars, DuckDB, Malloy, SQL Infrastructure-as-code: Terraform, Pulumi Data Management and Orchestration: Airflow, dbt Databases and Data Warehouses: SQL Server, PostgreSQL, MongoDB, Qdrant More ❯

drive organization-wide solutions Data & Analytics Specific Qualifications: Experience building enterprise-grade cloud-native and SaaS Data & Analytics platforms and solutions. Microsoft Azure experience is preferred. Experience with Snowflake, Databricks, Azure Data Factory and other Azure services, Tableau/Power BI Experience with Data Orchestration and Observability technologies and platforms Familiarity with Azure AI services (Azure Machine Learning, Azure Cognitive More ❯

depth experience with MS SQL Server and T-SQL is required. Experience with ETL tools such as SSIS and Azure Data Factory required. Experience with Data Engineering such as Databricks is required Experience with understanding and developing data lake/delta lake eco systems is required. Experience with working with large volumes of data millions of records Experience building and More ❯

Factory, Azure Blob Storage, and Azure SQL Database. Experience working with large datasets and complex data pipelines. Experience with data architecture design and data pipeline optimization. Proven expertise with Databricks, including hands-on implementation experience and certifications. Experience with SQL and NoSQL databases. Experience with data quality and data governance processes. Experience with version control systems (e.g., Git). Experience More ❯

to clean, transform, and enrich data from various sources. Ensure that pipelines are automated, scalable, and fault-tolerant to accommodate large volumes of data. Experience with Notebooks (e.g., Jupyter, Databricks) for data exploration, analysis, and reporting. Design and optimise data workflows to streamline key processing tasks, enhancing operational efficiency. API Integration & Data Ingestion: Integrate external and internal APIs to ingest More ❯

Airflow, dbt, Talend, AWS Glue, GCP Dataform/Cloud Composer) Proven ability to design, deploy, and optimize data warehouses and lakehouse architectures using technologies like BigQuery, Redshift, Snowflake, and Databricks Experience with Infrastructure as Code tools (e.g., Terraform, AWS CloudFormation, GCP Deployment Manager) for cloud resource provisioning and management Proficiency with CI/CD pipelines and DevOps practices for data More ❯

s degree in Computer Science, Data Science, or a related field. 8+ years of experience in data architecture and/or data engineering roles. Strong hands-on experience with Databricks and Power BI for data processing, analytics, and visualization. Expertise in cloud platforms such as Azure or AWS, including data storage, processing, and security features. Familiarity with data governance, compliance More ❯

product governance at the enterprise level. Preferred Skills Experience in Agile/Scrum environments with strong communication and stakeholder management skills. Familiarity with cloud-native platforms such as AWS, Databricks, Snowflake, and Azure Data Services. Familiarity with AI technologies, including Deep Learning, Machine Learning, Natural Language Processing (NLP), Large Language Models (LLMs), and related frameworks Familiarity with data quality tools More ❯

below; not required to have experience in all. Data Platforms: DW & lake concepts incl. dimensional modeling & cloud services (S3, AWS Redshift, RDS, Azure Data Lake Storage, Synapse Analytics, BigQuery, Databricks, Snowflake, Informatica); Databases: SQL & relational/non-relational (SQL Server, Oracle, PostgreSQL, MongoDB); BI Tools: Power BI, Business Objects, Tableau, Crystal, Looker; ETL/ELT: Cloud native (AWS Glue, Azure More ❯

or a related field Strong programming skills in Python and SQL Experience with Google Cloud Platform and/or Azure Cloud Services (DataFactory, Functions, SSIS) Hands-on experience with Databricks (GCP or Azure) Experience deploying and maintaining ML models (e.g., MLflow, Vertex AI, Azure ML) Beneficial Experience with Spark and other distributed data processing frameworks Exposure to MLOps tooling for More ❯

basis your varied role will include, but will not be limited to: Design, build, and optimize high-performance data pipelines and ETL workflows using tools like Azure Synapse, Azure Databricks or Microsoft Fabric. Implement scalable solutions to ingest, store, and transform vast datasets, ensuring data availability and quality across the organization. Write clean, efficient, and reusable Python code tailored to More ❯

or similar platforms. Strong understanding of data warehousing concepts, data modelling, and ETL processes. Strong understanding of SAP Datasphere and basic knowledge of SAP Business data cloud and Azure Databricks Excellent analytical and problem-solving skills, with the ability to work with complex data sets. Strong communication and interpersonal skills, with the ability to collaborate effectively with technical and non More ❯

Salary: 50.000 - 60.000 € per year Requirements: • 3+ years of hands-on experience as a Data Engineer working with Databricks and Apache Spark • Strong programming skills in Python, with experience in data manipulation libraries (e.g., PySpark, Spark SQL) • Experience with core components of the Databricks ecosystem: Databricks Workflows, Unity Catalog, and Delta Live Tables • Solid understanding of data warehousing principles, ETL … and German (min. B2 levels) • Ability to work independently as well as part of a team in an agile environment Responsibilities: As a Data Engineer with a focus on Databricks, you will play a key role in building modern, scalable, and high-performance data solutions for our clients. You'll be part of our growing Data & AI team and work … hands-on with the Databricks platform, supporting clients in solving complex data challenges. • Designing, developing, and maintaining robust data pipelines using Databricks, Spark, and Python • Building efficient and scalable ETL processes to ingest, transform, and load data from various sources (databases, APIs, streaming platforms) into cloud-based data lakes and warehouses • Leveraging the Databricks ecosystem (SQL, Delta Lake, Workflows, Unity More ❯

hands-on experience in enterprise data engineering and Azure cloud data technologies. You must be confident working across: Azure Data Services, including: Azure Data Factory Azure Synapse Analytics Azure Databricks Microsoft Fabric (desirable) Python and PySpark for data engineering, transformation, and automation ETL/ELT pipelines across diverse structured and unstructured data sources Data lakehouse and data warehouse architecture design More ❯

Promote user adoption, training, and change management initiatives Ensure high standards of documentation and data security compliance Technical Skills (desirable): Microsoft Azure Data Services (e.g., Azure Data Factory, Synapse, Databricks, Fabric) Data warehousing and lakehouse design ETL/ELT pipelines SQL, Python for data manipulation and machine learning Big Data frameworks (e.g., Hadoop, Spark) Data visualisation (e.g., Power BI) Understanding More ❯

Promote user adoption, training, and change management initiatives Ensure high standards of documentation and data security compliance Technical Skills (desirable): Microsoft Azure Data Services (e.g., Azure Data Factory, Synapse, Databricks, Fabric) Data warehousing and lakehouse design ETL/ELT pipelines SQL, Python for data manipulation and machine learning Big Data frameworks (e.g., Hadoop, Spark) Data visualisation (e.g., Power BI) Understanding More ❯

Promote user adoption, training, and change management initiatives Ensure high standards of documentation and data security compliance Technical Skills (desirable): Microsoft Azure Data Services (e.g., Azure Data Factory, Synapse, Databricks, Fabric) Data warehousing and lakehouse design ETL/ELT pipelines SQL, Python for data manipulation and machine learning Big Data frameworks (e.g., Hadoop, Spark) Data visualisation (e.g., Power BI) Understanding More ❯

as an Azure Data Architect or Lead Data Engineer. Expertise in Microsoft Fabric, as well as in one or more of the following platforms: Azure Synapse Analytics and Azure Databricks, and supporting data technologies like Power BI, Microsoft Purview, Azure SQL Database, Azure Data Lake, etc. Excellent stakeholder engagement and communication skills. Able to consult, advise, architect and estimate project More ❯