1 to 25 of 96 Remote Hadoop Jobs

S3, BigQuery, Redshift, Data Lakes). Expertise in SQL for querying large datasets and optimizing performance. Experience working with big data technologies such as Hadoop, Apache Spark, and other distributed computing frameworks. Solid understanding of machine learning algorithms, data preprocessing, model tuning, and evaluation. Experience in working with LLM More ❯

S3, BigQuery, Redshift, Data Lakes). Expertise in SQL for querying large datasets and optimizing performance. Experience working with big data technologies such as Hadoop, Apache Spark, and other distributed computing frameworks. Solid understanding of machine learning algorithms, data preprocessing, model tuning, and evaluation. Experience in working with LLM More ❯

proficiency in SQL and database management. Experience with cloud platforms such as AWS, Azure, or Google Cloud. Familiarity with Big Data technologies such as Hadoop, Spark, and Kafka is a plus. Excellent problem-solving and analytical skills. Strong communication and collaboration abilities. Experience with Python or other scripting languages. More ❯

large-scale data. Experience with ETL processes for data ingestion and processing. Proficiency in Python and SQL. Experience with big data technologies like Apache Hadoop and Apache Spark. Familiarity with real-time data processing frameworks such as Apache Kafka or Flink. MLOps & Deployment: Experience deploying and maintaining large-scale More ❯

Proven experience as a Data Engineer with a strong background in data pipelines. Proficiency in Python, Java, or Scala, and big data technologies (e.g., Hadoop, Spark, Kafka). Experience with Databricks, Azure AI Services, and cloud platforms (AWS, Google Cloud, Azure). Solid understanding of SQL and NoSQL databases. More ❯

years experience working on mission critical data pipelines and ETL systems, hands-on experience with big data technology, systems and tools such as AWS, Hadoop, Hive, and Snowflake Detailed problem-solving approach, coupled with a strong sense of ownership and drive A passionate bias to action and passion for More ❯

Familiarity with the Technology stack available in the industry for data management, data ingestion, capture, processing and curation: Kafka, StreamSets, Attunity, GoldenGate, Map Reduce, Hadoop, Hive, Hbase, Cassandra, Spark, Flume, Hive, Impala, etc. Familiarity with Networking, Windows/Linux virtual machines, Container, Storage, ELB, AutoScaling is a plus Experience More ❯

with programming languages such as Python or Java. Understanding of data warehousing concepts and data modeling techniques. Experience working with big data technologies (e.g., Hadoop, Spark) is an advantage. Excellent problem-solving and analytical skills. Strong communication and collaboration skills. Responsibilities: Design, build and maintain efficient and scalable data More ❯

with programming languages such as Python or Java. Understanding of data warehousing concepts and data modeling techniques. Experience working with big data technologies (e.g., Hadoop, Spark) is an advantage. Excellent problem-solving and analytical skills. Strong communication and collaboration skills. Benefits Enhanced leave - 38 days inclusive of 8 UK More ❯

experience in their technologies You have experience in database technologies including writing complex queries against their (relational and non-relational) data stores (e.g. Postgres, Hadoop, Elasticsearch, Graph databases), and designing the database schemas to support those queries You have a good understanding of coding best practices and design patterns More ❯

schemas for efficient querying. Implementing ETL/ELT pipelines to load and transform data in Snowflake. Big Data Processing Frameworks : Familiarity with Apache Spark , Hadoop, or other distributed data processing frameworks. Data Governance and Compliance : Understanding of data governance principles , security policies, and compliance standards (e.g., GDPR, HIPAA). More ❯

including data manipulation (Pandas, NumPy) and workflow management (Dask, PySpark, FastAPI). o Solid knowledge of cloud platforms (Azure, AWS) and big data technologies (Hadoop, Spark). o Hands-on experience with Docker, Kubernetes, and containerized environments. o Strong understanding of dimensional modeling (Kimball), relational database design (3NF), and More ❯

with have expertise in some of the following: Python, SQL, Scala, and Java for data engineering. Strong experience with big data tools (Apache Spark, Hadoop, Databricks, Dask) and cloud platforms (AWS, Azure, GCP). Proficient in data modelling (relational, NoSQL, dimensional) and DevOps automation (Docker, Kubernetes, Terraform, CI/ More ❯

implementing cloud based data solutions using AWS services such as EC2, S3, EKS, Lambda, API Gateway, Glue and bid data tools like Spark, EMR, Hadoop etc. Hands on experience on data profiling, data modeling and data engineering using relational databases like Snowflake, Oracle, SQL Server; ETL tools like Informatica More ❯

and guiding teams toward software development best practices Experience in SQL, NoSQL, Cypher and other big data querying languages Experience with big data frameworks (Hadoop, Spark, Flink etc.) Experience with ML lifecycle management tools (MLflow, Kubeflow, etc.) Familiarity with data pipelining and streaming technologies (Apache Kafka, Apache Nifi, etc. More ❯

infrastructure and its impact on data architecture. Data Technology Skills: 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. Exposure to ETL/ELT processes, SQL, NoSQL databases is a More ❯

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 More ❯

with unstructured datasets. Engineering best practices and standards. Experience with data warehouse software (e.g. Snowflake, Google BigQuery, Amazon Redshift). Experience with data tools: Hadoop, Spark, Kafka, etc. Code versioning (Github integration and automation). Experience with scripting languages such as Python or R. Working knowledge of message queuing More ❯

AWS Databases: MSSQL, PostgreSQL, MySQL, NoSQL Cloud: AWS (preferred), with working knowledge of cloud-based data solutions Nice to Have: Experience with graph databases, Hadoop/Spark, or enterprise data lake environments What You’ll Bring Strong foundation in computer science principles (data structures, algorithms, etc.) Experience building enterprise More ❯

AWS Databases: MSSQL, PostgreSQL, MySQL, NoSQL Cloud: AWS (preferred), with working knowledge of cloud-based data solutions Nice to Have: Experience with graph databases, Hadoop/Spark, or enterprise data lake environments What You’ll Bring Strong foundation in computer science principles (data structures, algorithms, etc.) Experience building enterprise More ❯

will be deployed You have experience in database technologies including writing complex queries against their (relational and non-relational) data stores (e.g. Postgres, Apache Hadoop, Elasticsearch, Graph databases), and designing the database schemas to support those queries You have a good understanding of coding best practices & design patterns and More ❯

The role We are looking for a Data Engineer to join the Data Science & Engineering team in London. Working at WGSN Together, we create tomorrow A career with WGSN is fast-paced, exciting and full of opportunities to grow and More ❯

recommending scalable, creative solutions. Exposure to some of the following technologies: Python, AWS Redshift, AWS Athena/Apache Presto, Big Data technologies (e.g S3, Hadoop, Hive, Spark, Flink, Kafka etc), NoSQL systems like Cassandra, DBT is nice to have. What you'll get: Full responsibility for projects from day More ❯

learn, standard libraries, etc.), Python packages that wrap Machine Learning (packages for NLP, Object Detection, etc.), Linux, AWS/C2S, Apache NiFi, Spark, pySpark, Hadoop, Kafka, ElasticSearch, Solr, Kibana, neo4J, MariaDB, Postgres, Docker, Puppet, and many others. Work on this program takes place in Chantilly, VA, McLean, VA and More ❯

learn, standard libraries, etc.), Python packages that wrap Machine Learning (packages for NLP, Object Detection, etc.), Linux, AWS/C2S, Apache NiFi, Spark, pySpark, Hadoop, Kafka, ElasticSearch, Solr, Kibana, neo4J, MariaDB, Postgres, Docker, Puppet, and many others. Work on this program takes place in Chantilly, VA, McLean, VA and More ❯