1 to 25 of 45 Remote Apache Spark Jobs

deliver reliable, high-performance data solutions using Databricks and modern cloud technologies. Key Responsibilities Design, develop, and maintain scalable data pipelines using Databricks, Apache Spark, and Delta Lake Build and optimize ETL/ELT workflows for batch and streaming data Develop data models to support analytics, reporting … data pipelines, architectures, and best practices Required Qualifications 3+ years of experience in data engineering or a similar role Strong experience with Databricks and Apache Spark Proficiency in Python and SQL Experience with Delta Lake, data modeling, and performance tuning Hands-on experience with cloud platforms (AWS, Azure ...

team members, building technical expertise and capability Key Responsibilities Develop production-ready data pipelines and processing jobs using batch and streaming frameworks such as Apache Spark and Apache Beam Apply expertise in data storage technologies including relational, columnar, document, NoSQL, data warehouses, and data lakes Implement modern ...

team members, building technical expertise and capability Key Responsibilities Develop production-ready data pipelines and processing jobs using batch and streaming frameworks such as Apache Spark and Apache Beam Apply expertise in data storage technologies including relational, columnar, document, NoSQL, data warehouses, and data lakes Implement modern ...

team members, building technical expertise and capability Key Responsibilities Develop production-ready data pipelines and processing jobs using batch and streaming frameworks such as Apache Spark and Apache Beam Apply expertise in data storage technologies including relational, columnar, document, NoSQL, data warehouses, and data lakes Implement modern ...

team members, building technical expertise and capability Key Responsibilities Develop production-ready data pipelines and processing jobs using batch and streaming frameworks such as Apache Spark and Apache Beam Apply expertise in data storage technologies including relational, columnar, document, NoSQL, data warehouses, and data lakes Implement modern ...

platform, features, and best practices with Strong understanding of data modeling principles and techniques A solid understanding of big data technologies such as Apache Spark, and knowledge of Hadoop ecosystems. Knowledge of programming languages such as Python, R, or Java is beneficial. Knowledge of ETL/ELT processes ...

practices, including ETL/ELT, data warehousing and data modelling. - Expertise in cloud data platforms, ideally Azure services such as Data Factory, Synapse, Databricks, Spark or Snowflake. - Proficiency in Python, SQL and other relevant languages for building pipelines and enabling automation. - Experience building and managing production data services, integrating ...

Seaborn) Ability to communicate complex analytical findings to diverse audiences Preferred Qualifications Experience with cloud platforms (AWS, GCP, Azure) Familiarity with big data technologies (Spark, Hadoop) Experience deploying models into production environments Knowledge of deep learning frameworks (TensorFlow, PyTorch) Experience working in Agile or cross-functional product teams ...

deliver intelligent data products, leveraging modern cloud and AI technologies. Key Responsibilities Design and implement robust data pipelines and ML workflows using Python, SQL, Spark, and Databricks. Develop and deploy machine learning models (including NLP, deep learning, and agentic AI) in production environments. Integrate data from diverse sources, including ...

seeking a Lead Data Engineering Consultant with proven experience in leading and developing data engineering platforms. Experience required: Extensive enterprise experience with Hadoop, Spark, and Splunk. Proficiency in object-oriented and functional scripting, particularly in Python. Skilled in handling raw, structured, semi-structured, and unstructured data (SQL and NoSQL ...

seeking a Lead Data Engineering Consultant with proven experience in leading and developing data engineering platforms. Experience required: Extensive enterprise experience with Hadoop, Spark, and Splunk. Proficiency in object-oriented and functional scripting, particularly in Python. Skilled in handling raw, structured, semi-structured, and unstructured data (SQL and NoSQL ...

integration. Proficiency with Databricks for data processing and analytics. Working knowledge of NodeJS would be an added advantage. Solid programming skills in Python , PySpark, Spark . Candidate must be adept at working with large-scale datasets , S3 , Python , and data cataloguing tools . Familiarity with data engineering best practices ...

Azure, utilizing managed services like SageMaker or Vertex AI. Data Foundations: Strong understanding of data modeling, feature stores, and distributed computing (e.g., Spark, Dask). Qualifications & Experience Experience: 5+ years in a software or data engineering role, with at least 3 years specifically focused on the deployment and scaling ...

leading and developing data engineering platforms. The ideal candidate will possess hands-on expertise in the following areas: Extensive enterprise experience with Hadoop, Spark, and Splunk. Proficiency in object-oriented and functional Scripting, particularly in Python. Skilled in handling raw, structured, semi-structured, and unstructured data (SQL and NoSQL ...

leading and developing data engineering platforms. The ideal candidate will possess hands-on expertise in the following areas: Extensive enterprise experience with Hadoop, Spark, and Splunk. Proficiency in object-oriented and functional scripting, particularly in Python. Skilled in handling raw, structured, semi-structured, and unstructured data (SQL and NoSQL ...

hedge fund, energy major or vendor serving these sectors. Knowledge of JavaScript frameworks, particularly React.js . Experience with Big Data technologies such as HDFS, Spark, Scala, Kudu, HBase, SQL, Impala , and traditional RDBMS. Quantitative skills in areas such as statistics, probability, optimization or derivative pricing. Some hands-on C++ ...

ONNX runtime). Familiar with AI tools like Cursor, Copilot, and Claude. Data Handling: Experience with big data technologies and tools such as Hadoop, Spark, or similar. Algorithm Knowledge: Good understanding of machine learning algorithms, natural language processing, and data mining techniques. Problem-Solving Skills: Demonstrated ability to solve ...

Azure or AWS Strong experience designing and delivering data solutions in Databricks Proficient with SQL and Python Experience using Big Data technologies such as Apache Spark or PySpark Great communication skills, effectively participating with Senior Stakeholders Nice to haves: Azure/AWS Data Engineering certifications Databricks certifications What ...

data governance, stewardship frameworks, and operating models Hands-on experience with data engineering and large-scale processing, including ETL/ELT, Python, and Spark Proven experience designing and operating modern cloud data platforms on Azure, including Fabric and Databricks Ability to design and govern secure, scalable, and resilient data ...

MLOps, model serving, scaling and monitoring workflows (e.g., BentoML, MLflow, Vertex AI, AWS Sagemaker) Experience building streaming + batch data ingestion and transformation pipelines (Spark/Airflow/Beam) Mobile and front-end web application development experience What We Offer At Newpage, we’re building a company that works ...

statistical modeling Experience with programming languages (Python, R, SQL) Strong understanding of data visualization tools (Tableau, Power BI) Experience with big data technologies (Hadoop, Spark) Strong understanding of data mining techniques and data modeling Excellent problem-solving and communication skills Qualifications Master's degree in Data Science, Computer Science ...

teams to drive outcomes Core skills (indicative) Production pipeline design and deployment experience Strong engineering capability with Python, SQL, plus big data tooling (e.g., Spark, and Java/Scala where relevant AWS, Azure, GCP Working pattern Hybrid working, with the team on client site or in the office ...

with Databricks** You'll play a pivotal role in designing, building, and optimising their Azure-based Data Lakehouse, with a focus on Databricks, PySpark, Spark SQL, and Azure Data Factory. This isn't just about coding - you'll also provide architectural guidance, mentor engineers, and ensure solutions are scalable ...

with Databricks** You'll play a pivotal role in designing, building, and optimising their Azure-based Data Lakehouse, with a focus on Databricks, PySpark, Spark SQL, and Azure Data Factory. This isn't just about coding - you'll also provide architectural guidance, mentor engineers, and ensure solutions are scalable ...

from classical statistics and regression to deep learning and NLP. Data Engineering: Proficiency in SQL and experience working with modern data stacks (e.g., Snowflake, Spark, or cloud-native tools on AWS/GCP/Azure). Scientific Rigor: A strong foundation in the scientific methodforming hypotheses, designing experiments ...