1 to 25 of 124 Remote Apache Spark Jobs

focus, you will be an integral part of our team dedicated to building scalable and secure data platforms. You will combine deep Databricks and Apache Spark expertise with strong client engagement skills to shape solutions from early-stage opportunity through delivery. You will lead our Databricks partnership activity … sales by contributing to discovery, solution design, estimates, and compelling client-facing materials. Design and build high-performance data platforms: Utilize Databricks and Apache Spark to extract, transform, and load data across cloud and on-premises sources and targets. Design and oversee the delivery of secure data warehouses ...

should have specialist experience in one or more of the following technologies Azure Databricks Design and build high-performance data pipelines: Utilize Databricks and Apache Spark to extract, transform, and load data into Azure Data Lake Storage and other Azure services. Experience of Databricks ML and Azure … develop predictive models and drive business insights. Proven expertise in Databricks, Apache Spark, and data pipeline development and strong understanding of data warehousing concepts and practices. Experience with Microsoft Azure cloud platform, including Azure Data Lake Storage, Databricks and Azure Data Factory. Azure Data Engineer Associate and Databricks ...

will be an integral part of our team dedicated to building scalable and secure data platforms. You will leverage your expertise in Databricks, Apache Spark, and Azure to design, develop, and implement data warehouses, data lakehouses, and AI/ML models that fuel our data-driven operations. What … which Azure data focused components to use for which purpose. Microsoft certified architect Databricks Design and build high-performance data platforms: Utilize Databricks and Apache Spark to extract, transform, and load data into Azure Data Lake Storage and other Azure services. Ability to Design, Build and deploy ...

designing and delivering modern data platforms, working closely with clients and technical teams to build scalable, secure and high-performing solutions using Databricks, Apache Spark and cloud technologies. Key Responsibilities Design and architect Databricks-based data platforms and solutions. Build scalable data lakehouse and data warehouse architectures. Design … Databricks and modern data platform delivery. Skills & Experience Required 7+ years' experience in Data Architecture or Solution Architecture. Strong commercial experience with Databricks and Apache Spark . Experience delivering enterprise data platforms on AWS, Azure or GCP. Strong understanding of data warehousing, data lakes and lakehouse architectures. Experience ...

designing and delivering modern data platforms, working closely with clients and technical teams to build scalable, secure and high-performing solutions using Databricks, Apache Spark and cloud technologies. You'll also play a key role in pre-sales activities, solution design, and helping to drive strategic Databricks initiatives … Databricks and modern data platform delivery. Skills & Experience Required 7+ years' experience in Data Architecture or Solution Architecture. Strong commercial experience with Databricks and Apache Spark . Experience delivering enterprise data platforms on AWS, Azure or GCP. Strong understanding of data warehousing, data lakes and lakehouse architectures. Experience ...

data lakes, operational data stores, event streaming platforms, and real-time data pipelines. Architect and document solutions using technologies such as Hive, Impala, HBase, Spark, NiFi, Flink, Kafka, and equivalent AWS services. Design Kafka-based streaming applications, including event ingestion, topic design, consumer patterns, error handling, replay, scalability …/CDP or equivalent big data platforms. Strong demonstrable experience with some of the distributed data technologies (if not all) such as: HBase Spark NiFi Kafka Flink Hive Impala Experience designing and delivering large-scale data ingestion, transformation, storage, and consumption patterns. Experience with Kafka consumer architecture, including consumer ...

Python, Java or Scala, and SQL. Hands‐on experience building and operating large‐scale data pipelines using big data and distributed processing technologies (e.g. Apache Spark, Hadoop). Experience designing and maintaining data lakes, distributed storage platforms, and data pipeline orchestration tools. Experience working with cloud‐native data ...

Python, Java or Scala, and SQL. Hands‐on experience building and operating large‐scale data pipelines using big data and distributed processing technologies (e.g. Apache Spark, Hadoop). Experience designing and maintaining data lakes, distributed storage platforms, and data pipeline orchestration tools. Experience working with cloud‐native data ...

Python, Java or Scala, and SQL. Hands‐on experience building and operating large‐scale data pipelines using big data and distributed processing technologies (e.g. Apache Spark, Hadoop). Experience designing and maintaining data lakes, distributed storage platforms, and data pipeline orchestration tools. Experience working with cloud‐native data ...

Python, Java or Scala, and SQL. Hands‐on experience building and operating large‐scale data pipelines using big data and distributed processing technologies (e.g. Apache Spark, Hadoop). Experience designing and maintaining data lakes, distributed storage platforms, and data pipeline orchestration tools. Experience working with cloud‐native data ...

Python, Java or Scala, and SQL. Hands‐on experience building and operating large‐scale data pipelines using big data and distributed processing technologies (e.g. Apache Spark, Hadoop). Experience designing and maintaining data lakes, distributed storage platforms, and data pipeline orchestration tools. Experience working with cloud‐native data ...

Python, Java or Scala, and SQL. Hands‐on experience building and operating large‐scale data pipelines using big data and distributed processing technologies (e.g. Apache Spark, Hadoop). Experience designing and maintaining data lakes, distributed storage platforms, and data pipeline orchestration tools. Experience working with cloud‐native data ...

Python, Java or Scala, and SQL. Hands‐on experience building and operating large‐scale data pipelines using big data and distributed processing technologies (e.g. Apache Spark, Hadoop). Experience designing and maintaining data lakes, distributed storage platforms, and data pipeline orchestration tools. Experience working with cloud‐native data ...

Python, Java or Scala, and SQL. Hands on experience building and operating large scale data pipelines using big data and distributed processing technologies (e.g. Apache Spark, Hadoop). Experience designing and maintaining data lakes, distributed storage platforms, and data pipeline orchestration tools. Experience working with cloud native data ...

Python, Java or Scala, and SQL. Hands on experience building and operating large scale data pipelines using big data and distributed processing technologies (e.g. Apache Spark, Hadoop). Experience designing and maintaining data lakes, distributed storage platforms, and data pipeline orchestration tools. Experience working with cloud native data ...

considering: We are looking for an experienced AWS Databricks Engineer with strong hands-on expertise in Databricks, AWS cloud services, PySpark, Spark SQL, Delta Lake, Python, SQL, and data engineering. The candidate will be responsible for designing, developing, optimizing, and supporting scalable data pipelines and Lakehouse solutions … forums, architecture review boards, design authority meetings, and client stakeholder workshops. Your Skills: Strong hands-on experience with Databricks on AWS. Strong experience with Apache Spark/PySpark. Excellent programming skills in Python. Strong SQL skills including complex queries, joins, CTEs, window functions, and query optimization. AWS Secrets ...

lead quality assurance and testing activities within a large-scale cloud data engineering programme operating across a modern AWS-native technology ecosystem, including Apache Airflow, Amazon Athena, AWS Glue, S3, EMR, DynamoDB, and related cloud services. This role combines hands-on technical leadership with test strategy ownership . … reconciliation, and performance under load Oversee PySpark-based data validation and interrogation activities on AWS EMR Support testing and monitoring of workflows orchestrated through Apache Airflow Drive root cause analysis for production data issues and platform defects Risk Management & Reporting Identify, assess, and communicate quality risks across releases ...

considering: We are looking for an experienced AWS Databricks Engineer with strong hands-on expertise in Databricks, AWS cloud services, PySpark, Spark SQL, Delta Lake, Python, SQL, and data engineering. The candidate will be responsible for designing, developing, optimizing, and supporting scalable data pipelines and lakehouse solutions … time. Your Role: Design, develop, and maintain scalable data pipelines using Databricks on AWS. Build and optimize data processing frameworks using PySpark, Spark SQL, Python, Delta Lake, and Databricks notebooks. Develop end-to-end ETL/ELT pipelines for ingestion, transformation, validation, and consumption. Work with AWS services such ...

Databricks, Azure Data Factory (ADF), and ADLS Gen2. Expertise in designing scalable, resilient, and enterprise-grade Azure data solutions. Advanced proficiency in PySpark, Python, Spark SQL, and SQL. Strong experience with SQL optimization, performance tuning, joins, window functions, and stored procedures. Extensive experience in developing and optimizing large-scale ...

version control. Data Engineering Stack Experience building pipelines using streaming frameworks, distributed processing engines and relational or analytical storage technologies. Examples include Kafka, Spark, PostgreSQL. Orchestration Experience defining and running data workflows using modern orchestration frameworks. Examples include Airflow, Dagster or Prefect. Data Quality and Lineage Familiarity with tools ...

native solutions that support analytics, automation, and digital transformation. Data Engineering, Full Stack & Platform Development Design and implement scalable data pipelines using tools like Apache Spark, Airflow, or dbt.Build and maintain data lakes, warehouses, and real-time streaming solutions. Develop APIs and microservices to expose data securely ...

strategic thinking. Essential Skills & Experience Strong Microsoft Fabric expertise (Lakehouse, Warehouse, Pipelines, Notebooks) OneLake architecture and management Advanced SQL/T-SQL PySpark and Spark optimisation Data warehousing, modelling and ETL/ELT development Power BI semantic modelling Experience delivering enterprise cloud data platforms Experience integrating multiple business systems ...

Exceptional programming skills in Python, with a command of data science libraries (e.g., Pandas, NumPy, Scikit‐learn). Experience with big data technologies (e.g., Spark, Trino, Hadoop) and ideally cloud platforms (e.g., AWS, GCP, Azure) for scalable data processing, storage, and model deployment. Ideally having understanding and practical experience ...

PostgreSQL (or similar relational databases) and NoSQL databases. Experience with vector databases such as Qdrant, Milvus or pgvector . Familiarity with technologies such as Apache Spark, Airflow, Kafka, Elasticsearch/OpenSearch, Pandas and Polars . Strong understanding of data modelling, storage architecture and performance optimisation. Desirable Experience working ...

data models and ETL processes, to support the construction of scalable and efficient data systems. Familiarity with big data tools like DuckDB, Polars or Apache Spark for processing out-of-memory datasets" . Proven experience collaborating with first-team stakeholders within a professional sports environment, demonstrating strong interpersonal ...