implementation of modern data architectures (ideally Azure, AWS. Microsoft Fabric, GCP, Data Factory) and modern data warehouse technologies (Snowflake, Databricks) Experience with database technologies such as SQL, NoSQL, Oracle, Hadoop, or Teradata Ability to collaborate within and across teams of different technical knowledge to support delivery and educate end users on data products Expert problem-solving skills, including debugging More ❯
of the following: Python, SQL, Java Commercial experience in client-facing projects is a plus, especially within multi-disciplinary teams Deep knowledge of database technologies: Distributed systems (e.g., Spark, Hadoop, EMR) RDBMS (e.g., SQL Server, Oracle, PostgreSQL, MySQL) NoSQL (e.g., MongoDB, Cassandra, DynamoDB, Neo4j) Solid understanding of software engineering best practices - code reviews, testing frameworks, CI/CD, and More ❯
pipelines and ETL - informatica - Experience in SQL and database management systems - Knowledge of data modelling , warehousing concepts , and ETL processes - Experience with big data technologies and frameworks such as Hadoop, Hive, Spark. Programming experience in Python or Scala. - Demonstrated analytical and problem-solving skills. - Familiarity with cloud platforms (e.g Azure , AWS ) and their data related services - Proactive and detail More ❯
desirable. Experience: 3-6 years of relevant work experience in healthcare. Previous experience with Epic Cognitive Computing and Epic certifications. Data modeling experience. Experience with big data technologies (e.g., Hadoop, Spark) preferred. Experience with cloud computing platforms (e.g., AWS, Azure, Google Cloud, and Databricks). Experience with Linux and familiar with concepts of HDA, slate, and docker. Level II More ❯
supervised, unsupervised, reinforcement learning), deep learning, and neural networks. Experience with data preprocessing, feature engineering, and model evaluation techniques.\Familiarity with data management and big data technologies (e.g., Spark, Hadoop, SQL, NoSQL databases). Knowledge of cloud platforms (e.g., AWS, Azure, GCP) and their AI/ML services. Strong analytical and problem-solving skills. Excellent communication and collaboration skills More ❯
Liverpool, Merseyside, North West, United Kingdom Hybrid / WFH Options
Forward Role
both relational databases (SQL Server, MySQL) and NoSQL solutions (MongoDB, Cassandra) Hands-on knowledge of AWS S3 and associated big data services Extensive experience with big data technologies including Hadoop and Spark for large-scale dataset processing Deep understanding of data security frameworks, encryption protocols, access management and regulatory compliance Proven track record building automated, scalable ETL frameworks and More ❯
clusting, dimensionality reduction, deep learning architectures). Experience with data preprocessing, feature engineering, and data visualization techniques. Familiarity with data storage and processing technologies (e.g., SQL, NoSQL databases, Spark, Hadoop). Experience with cloud platforms (e.g., AWS, Azure, GCP) and their machine learning services. Understanding of software development principles, version control (e.g., Git), and CI/CD pipelines. Strong More ❯
from you: Proficiency with the Python and SQL programming languages. Hands-on experience with cloud platforms like AWS, GCP, or Azure, and familiarity with big data technologies such as Hadoop or Spark. Experience working with relational databases and NoSQL databases. Strong knowledge of data structures, data modelling, and database schema design. Experience in supporting data science workloads and working More ❯
AI/ML technologies (e.g., TensorFlow, PyTorch, Scikit-learn, Keras) and understanding of deep learning and natural language processing (NLP). • Strong understanding of big data platforms such as Hadoop, Apache Spark, and data lakes. • Hands-on experience with cloud platforms (Azure, AWS, or Google Cloud) for building scalable data solutions. • Proficiency in data modeling, data warehousing, and ETL More ❯
as Python, Java, or C++. Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn). Familiarity with data processing tools and platforms (e.g., SQL, Apache Spark, Hadoop). Knowledge of cloud computing services (e.g., AWS, Google Cloud, Azure) and containerization technologies (e.g., Docker, Kubernetes) is a plus. Hugging Face Ecosystem: Demonstrated experience using Hugging Face tools More ❯
skills. Experience working in BFSI or enterprise-scale environments is a plus. Preferred: Exposure to cloud platforms (AWS, Azure, GCP) and their data services. Knowledge of Big Data platforms (Hadoop, Spark, Snowflake, Databricks). Familiarity with data governance and data catalog tools. More ❯
skills. Experience working in BFSI or enterprise-scale environments is a plus. Preferred: Exposure to cloud platforms (AWS, Azure, GCP) and their data services. Knowledge of Big Data platforms (Hadoop, Spark, Snowflake, Databricks). Familiarity with data governance and data catalog tools. More ❯
Bethesda, Maryland, United States Hybrid / WFH Options
Gridiron IT Solutions
Python, SCALA, and/or UNIX shell scripting Expertise in machine learning techniques and statistical analysis Proficiency in SQL and NoSQL databases Experience with big data platforms such as Hadoop, Spark, and Kafka Cloud computing expertise across AWS, Azure, and other Experience in designing and implementing real-time data processing solutions Strong understanding of AI/ML applications in More ❯
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 Maintaining the ApacheHadoop Ecosystem, especially utilizing HBase, MapReduce, and Spark. ETL processes utilizing Linux shell scripting, Perl, Python, and Apache Airflow. AWS services such as CloudWatch, CloudTrail, ELB, EMR, KMS, SQS, SNS More ❯
Open AI Services). Experience with PostgreSQL, ElasticSearch, MongoDB, and graph databases. Experience with GenAI enabled daily workflows (coding, testing, analytics). Experience with one or more SQL-on-Hadoop technology (Spark SQL, Hive, Impala, Presto, etc.) Experience with short-release cycles and the full software lifecycle Experience with Agile development methodology (e.g., Scrum) Current Security+ certification (or must More ❯
capability in documenting high-level designs, system workflows, and technical specifications. Deep understanding of architectural patterns (e.g., microservices, layered, serverless). Expert knowledge of big data tools (Kafka, Spark, Hadoop) and major cloud platforms (AWS, Azure, GCP) to inform technology recommendations. Proficiency in Java, C#, Python, or JavaScript/TypeScript. Experience with cloud platforms (AWS, Azure, Google Cloud) and More ❯
and complex technical projects to senior-level audiences. Coach direct and indirect reports on personal growth and analytical skills by conducting training on leading analytical tools and techniques including Hadoop, Hive, Python, R, SAS, Scala, Spark, Power BI and SQL. This position will require up to 10% travel within the U.S. to client sites and other EXL offices. Position More ❯
and manage data analytic frameworks and pipelines using databases and tools such as (but not limited to) NoSQL, SQL, NiFi, Kafka, HDInsight, MongoDB, Cassandra, Neo4j, GraphDB, OrientDB, Spark, Flink, Hadoop, Kafka, Hive, and others. • Apply distributed systems concepts and principles such as consistency and availability, liveness and safety, durability, reliability, fault-tolerance, consensus algorithms. • Administrate cloud computing and CI More ❯
to translate complex technical problems into business solutions. 🌟 It’s a Bonus If You Have: Experience in SaaS, fintech, or software product companies. Knowledge of big data frameworks (Spark, Hadoop) or cloud platforms (AWS, GCP, Azure). Experience building and deploying models into production. A strong interest in AI, automation, and software innovation. 🎁 What’s in It for You More ❯
to translate complex technical problems into business solutions. 🌟 It’s a Bonus If You Have: Experience in SaaS, fintech, or software product companies. Knowledge of big data frameworks (Spark, Hadoop) or cloud platforms (AWS, GCP, Azure). Experience building and deploying models into production. A strong interest in AI, automation, and software innovation. 🎁 What’s in It for You More ❯
to translate complex technical problems into business solutions. 🌟 It’s a Bonus If You Have: Experience in SaaS, fintech, or software product companies. Knowledge of big data frameworks (Spark, Hadoop) or cloud platforms (AWS, GCP, Azure). Experience building and deploying models into production. A strong interest in AI, automation, and software innovation. 🎁 What’s in It for You More ❯
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 of statistical analysis and predictive modelling Experience: 5+ years working with Microsoft data platforms 5+ years in a customer-facing consulting or More ❯
Reading, England, United Kingdom Hybrid / WFH Options
HD TECH Recruitment
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 of statistical analysis and predictive modelling Experience: 5+ years working with Microsoft data platforms 5+ years in a customer-facing consulting or More ❯
slough, south east england, united kingdom Hybrid / WFH Options
HD TECH Recruitment
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 of statistical analysis and predictive modelling Experience: 5+ years working with Microsoft data platforms 5+ years in a customer-facing consulting or More ❯
