1 to 25 of 80 Apache Spark Jobs in Berkshire

like S3, Lambda, BigQuery, or Databricks. Solid understanding of ETL processes , data modeling, and data warehousing. Familiarity with SQL and relational databases. Knowledge of big data technologies , such as Spark, Hadoop, or Kafka, is a plus. Strong problem-solving skills and the ability to work in a collaborative team environment. Excellent verbal and written communication skills. Bachelor's degree More ❯

Databricks platform. Optimise data pipelines for performance, efficiency, and cost-effectiveness. Implement data quality checks and validation rules within data pipelines. Data Transformation & Processing: Implement complex data transformations using Spark (PySpark or Scala) and other relevant technologies. Develop and maintain data processing logic for cleaning, enriching, and aggregating data. Ensure data consistency and accuracy throughout the data lifecycle. Azure … Databricks Implementation: Work extensively with Azure Databricks Unity Catalog, including Delta Lake, Spark SQL, and other relevant services. Implement best practices for Databricks development and deployment. Optimise Databricks workloads for performance and cost. Need to program using the languages such as SQL, Python, R, YAML and JavaScript Data Integration: Integrate data from various sources, including relational databases, APIs, and … best practices. Essential Skills & Experience: 10+ years of experience in data engineering, with at least 3+ years of hands-on experience with Azure Databricks. Strong proficiency in Python and Spark (PySpark) or Scala. Deep understanding of data warehousing principles, data modelling techniques, and data integration patterns. Extensive experience with Azure data services, including Azure Data Factory, Azure Blob Storage More ❯

independently and as part of a team. Preferred Qualifications: Master's degree in Computer Science, Data Science, or a related field. Experience with big data technologies such as Hadoop, Spark, or Kafka. Experience with data visualization tools such as Power BI, Tableau, or Qlik. Certifications in Azure data and AI technologies. Benefits We offer a competitive, market-aligned salary More ❯

in data engineering, architecture, or platform management roles, with 5+ years in leadership positions. Expertise in modern data platforms (e.g., Azure, AWS, Google Cloud) and big data technologies (e.g., Spark, Kafka, Hadoop). Strong knowledge of data governance frameworks, regulatory compliance (e.g., GDPR, CCPA), and data security best practices. Proven experience in enterprise-level architecture design and implementation. Hands More ❯

tools like Collibra, Alation, Microsoft Purview, or Informatica, including projects around lineage, cataloging, and quality rules. Strong hands-on development experience in SQL and Python, with working knowledge of Spark or other distributed data processing frameworks. Design, development and implementation of distributed data solutions using API and microservice-based architecture. Deep understanding of ETL/ELT architecture, streaming, and More ❯

with SQL, NoSQL, and data visualization tools. Strong analytical and problem-solving skills. Experience with social media analytics and user behavior analysis. Knowledge of big data technologies like Hadoop, Spark, Kafka. Familiarity with AWS machine learning services such as SageMaker and Comprehend. Understanding of data governance and security in AWS. Excellent communication and teamwork skills. Attention to detail and More ❯

with the ability to influence others Skills and Abilities Platforms & Tools Languages: Python, SQL, T-SQL, SSIS Methodologies: Agile, DevOps must have Concepts: ELT/ETL, DWH, APIs (RESTful), Spark APIs, FTP protocols, SSL, SFTP, PKI (public Key Infrastructure) and Integration testing Management Duties Yes We are an equal opportunity employer, and we are proud to share that More ❯

technologies – Azure, AWS, GCP, Snowflake, Databricks Must Have Hands on experience on at least 2 Hyperscalers (GCP/AWS/Azure platforms) and specifically in Big Data processing services (Apache Spark, Beam or equivalent). In-depth knowledge on key technologies like Big Query/Redshift/Synapse/Pub Sub/Kinesis/MQ/Event Hubs … minimum of 5 years’ experience in a similar role. Ability to lead and mentor the architects. Required Skills : Mandatory Skills [at least 2 Hyperscalers]: GCP, AWS, Azure, Big data, Apache spark, beam on BigQuery/Redshift/Synapse, Pub Sub/Kinesis/MQ/Event Hubs, Kafka Dataflow/Airflow/ADF. Preferred Skills : Designing Databricks based More ❯

technologies – Azure, AWS, GCP, Snowflake, Databricks Must Have Hands on experience on at least 2 Hyperscalers (GCP/AWS/Azure platforms) and specifically in Big Data processing services (Apache Spark, Beam or equivalent). In-depth knowledge on key technologies like Big Query/Redshift/Synapse/Pub Sub/Kinesis/MQ/Event Hubs … skills. A minimum of 5 years’ experience in a similar role. Ability to lead and mentor the architects. Mandatory Skills [at least 2 Hyperscalers] GCP, AWS, Azure, Big data, Apache spark, beam on BigQuery/Redshift/Synapse, Pub Sub/Kinesis/MQ/Event Hubs, Kafka Dataflow/Airflow/ADF Desirable Skills: Designing Databricks based More ❯

orchestration (e.g., Kubernetes). Preferred Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases). Experience with model explainability techniques (e.g. … SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

orchestration (e.g., Kubernetes). Preferred Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases). Experience with model explainability techniques (e.g. … SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

the Databricks Lakehouse Platform. Architectural Design: Lead the end-to-end design of the Databricks Lakehouse architecture (Medallion architecture), including data ingestion patterns, storage layers (Delta Lake), processing frameworks (Spark), and consumption mechanisms. Technology Selection: Evaluate and recommend optimal Databricks features and integrations (e.g., Unity Catalog, Photon, Delta Live Tables, MLflow) and complementary cloud services (e.g., Azure Data Factory … long-term sustainability of the platform. Required Skills & Experience Proven Databricks Expertise: Deep, hands-on experience designing and implementing solutions on the Databricks Lakehouse Platform (Delta Lake, Unity Catalog, Spark, Databricks SQL Analytics). Cloud Data Architecture: Extensive experience with Azure data services (e.g., Azure Data Factory, Azure Data Lake Storage, Azure Synapse) and architecting cloud-native data platforms. More ❯

teams . Preferred Skills High-Performance Computing (HPC) and AI workloads for large-scale enterprise solutions. NVIDIA CUDA, cuDNN, TensorRT experience for deep learning acceleration. Big Data platforms (Hadoop, Spark) for AI-driven analytics in professional services. Pls share CV at payal.c@hcltech.com More ❯

programming language (Python, Java, or Scala) Extensive experience with cloud platforms (AWS, GCP, or Azure) Experience with: Data warehousing and lake architectures SQL and NoSQL databases Distributed computing frameworks (Spark, Kinesis etc) Software development best practices including CI/CD, TDD and version control. Strong understanding of data modelling and system architecture Excellent problem-solving and analytical skills Whilst More ❯

with Big Data. Must know modern cloud platforms including Azure, GCP, etc and technologies across traditional and contemporary software, with focus as below:Expert understanding: Azure Data Factory, Databricks, Spark, Azure SQL Database, Azure DevOps/Git, Data Lake, Delta Lake/Lakehouse architecture, Power BI.Working Knowledge: Azure WebApp, Azure Networking concepts.Conceptual Knowhow (nice to have): Azure AI Services More ❯

technologies – Azure, AWS, GCP, Snowflake, Databricks Must Have Hands on experience on at least 2 Hyperscalers (GCP/AWS/Azure platforms) and specifically in Big Data processing services (Apache Spark, Beam or equivalent). In-depth knowledge on key technologies like Big Query/Redshift/Synapse/Pub Sub/Kinesis/MQ/Event Hubs … skills. A minimum of 5 years’ experience in a similar role. Ability to lead and mentor the architects. Mandatory Skills [at least 2 Hyperscalers] GCP, AWS, Azure, Big data, Apache spark, beam on BigQuery/Redshift/Synapse, Pub Sub/Kinesis/MQ/Event Hubs, Kafka Dataflow/Airflow/ADF Desirable Skills Designing Databricks based More ❯

technologies – Azure, AWS, GCP, Snowflake, Databricks Must Have Hands on experience on at least 2 Hyperscalers (GCP/AWS/Azure platforms) and specifically in Big Data processing services (Apache Spark, Beam or equivalent). In-depth knowledge on key technologies like Big Query/Redshift/Synapse/Pub Sub/Kinesis/MQ/Event Hubs … skills. A minimum of 5 years’ experience in a similar role. Ability to lead and mentor the architects. Mandatory Skills [at least 2 Hyperscalers] GCP, AWS, Azure, Big data, Apache spark, beam on BigQuery/Redshift/Synapse, Pub Sub/Kinesis/MQ/Event Hubs, Kafka Dataflow/Airflow/ADF Desirable Skills Designing Databricks based More ❯

data programs. 5+ years of advanced expertise in Google Cloud data services: Dataproc, Dataflow, Pub/Sub, BigQuery, Cloud Spanner, and Bigtable. Hands-on experience with orchestration tools like Apache Airflow or Cloud Composer. Hands-on experience with one or more of the following GCP data processing services: Dataflow (Apache Beam), Dataproc (Apache Spark/Hadoop … or Composer (Apache Airflow). Proficiency in at least one scripting/programming language (e.g., Python, Java, Scala) for data manipulation and pipeline development. Scala is mandated in some cases. Deep understanding of data lakehouse design, event-driven architecture, and hybrid cloud data strategies. Strong proficiency in SQL and experience with schema design and query optimization for large datasets. More ❯

platform teams at scale, ideally in consumer-facing or marketplace environments. Strong knowledge of distributed systems and modern data ecosystems, with hands-on experience using technologies such as Databricks, Apache Spark, Apache Kafka, and DBT. Proven success in building and managing data platforms supporting both batch and real-time processing architectures. Deep understanding of data warehousing, ETL More ❯

data pipelines and systems Qualifications & Skills: x5 + experience with Python programming for data engineering tasks Strong proficiency in SQL and database management Hands-on experience with Databricks and Apache Spark Familiarity with Azure cloud platform and related services Knowledge of data security best practices and compliance standards Excellent problem-solving and communication skills Multi-Year Project - Flexible More ❯

agile environment to deliver data solutions that support key firm initiatives. Build scalable and efficient batch and streaming data workflows within the Azure ecosystem. Apply distributed processing techniques using Apache Spark to handle large datasets effectively. Help drive improvements in data quality, implementing validation, cleansing, and monitoring frameworks. Contribute to the firm’s efforts around data security, governance More ❯

at Zodiac Maritime while working with cutting-edge cloud technologies. Key responsibilities and primary deliverables Design, develop, and optimize end-to-end data pipelines (batch & streaming) using Azure Databricks, Spark, and Delta Lake. Implement Medallion Architecture to structure raw, enriched, and curated data layers efficiently. Build scalable ETL/ELT processes with Azure Data Factory and PySpark. Work with … reliability across pipelines. Collaborate with analysts to validate and refine datasets for reporting. Apply DevOps & CI/CD best practices (Git, Azure DevOps) for automated testing and deployment. Optimize Spark jobs, Delta Lake tables, and SQL queries for performance and cost efficiency. Troubleshoot and resolve data pipeline issues proactively. Partner with Data Architects, Analysts, and Business Teams to deliver More ❯

Mathematics, Finance, etc. Proficiency in Python, SQL , and one or more: R, Java, Scala Experience with relational/NoSQL databases (e.g., PostgreSQL, MongoDB) Familiarity with big data tools (Hadoop, Spark, Kafka), cloud platforms (Azure, AWS, GCP), and workflow tools (Airflow, Luigi) Bonus: experience with BI tools , API integrations , and graph databases Why Join Us? Work with large-scale, high More ❯

SQL and database technologies (incl. various Vector Stores and more traditional technologies e.g. MySQL, PostgreSQL, NoSQL databases). − Hands-on experience with data tools and frameworks such as Hadoop, Spark, or Kafka - advantage − Familiarity with data warehousing solutions and cloud data platforms. − Background in building applications wrapped around AI/LLM/mathematical models − Ability to scale up algorithms More ❯

in Microsoft Azure is mandatory including components like Azure Data Factory, Azure Data Lake Storage, Azure SQL, Azure DataBricks, HD Insights, ML Service etc. Good knowledge of Python and Spark are required. Experience in ETL & ELT Good understanding of one scripting language Good understanding of how to enable analytics using cloud technology and ML Ops Experience in Azure Infrastructure More ❯