Java 5+ years of experience with a public cloud (AWS, Microsoft Azure, Google Cloud) 5+ years experience with Distributed data/computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Databricks) 4+ year experience working on real-time data and streaming applications 4+ years of experience with NoSQL implementation 4+ 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 ❯
City of London, London, United Kingdom Hybrid / WFH Options
McCabe & Barton
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 ❯
on mission critical data pipelines and ETL systems. 5+ years of hands-on experience with big data technology, systems and tools such as AWS, Hadoop, Hive, and Snowflake Expertise with common Software Engineering languages such as Python, Scala, Java, SQL and a proven ability to learn new programming languages More ❯
Experience with ETL processes and tools. Knowledge of cloud platforms (e.g., GCP, AWS, Azure) and their data services. Familiarity with big data technologies (e.g., Hadoop, Spark) is a plus. Understanding of AI tools like Gemini and ChatGPT is also a plus. Excellent problem-solving and communication skills. Ability to 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 ❯
Chantilly, Virginia, United States Hybrid / WFH Options
Aerospace Corporation
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 ❯
. Data Platforms: Warehouses: Snowflake, Google BigQuery, or Amazon Redshift. Analytics: Tableau, Power BI, or Looker for client reporting. Big Data: Apache Spark or Hadoop for large-scale processing. AI/ML: TensorFlow or Databricks for predictive analytics. Integration Technologies: API Management: Apigee, AWS API Gateway, or MuleSoft. Middleware More ❯
. Data Platforms: Warehouses: Snowflake, Google BigQuery, or Amazon Redshift. Analytics: Tableau, Power BI, or Looker for client reporting. Big Data: Apache Spark or Hadoop for large-scale processing. AI/ML: TensorFlow or Databricks for predictive analytics. Integration Technologies: API Management: Apigee, AWS API Gateway, or MuleSoft. Middleware More ❯
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 More ❯
experience in data engineering, including working with AWS services. Proficiency in AWS services like S3, Glue, Redshift, Lambda, and EMR. Knowledge of Cloudera-based Hadoop is a plus. Strong ETL development skills and experience with data integration tools. Knowledge of data modeling, data warehousing, and data transformation techniques. Familiarity More ❯
in data warehousing and business intelligence for utilities. • Knowledge of machine learning applications in predictive maintenance and energy forecasting. • Familiarity with Big Data technologies (Hadoop, Spark) and real-time streaming (Kafka). • Expertise in data modeling tools such as Erwin, IBM Data Architect, or PowerDesigner. • Strong knowledge of utility More ❯
Experience completing Databricks development and/or administrative tasks • Familiarity with some of these tools: DB2, Oracle, SAP, Postgres, Elastic Search, Glacier, Cassandra, DynamoDB, Hadoop, Splunk, SAP HANA, Databricks • Experience working with federal government clients Security Clearance: Active CBP Public Trust required SALARY RANGE: $130,000 to More ❯
Java 2+ years of experience with a public cloud (AWS, Microsoft Azure, Google Cloud) 3+ years experience with Distributed data/computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL) 2+ year experience working on real-time data and streaming applications 2+ years of experience with NoSQL More ❯
a Data Engineer for Cloud Data Lake activities, especially in high-volume data processing frameworks, ETL development using distributed computing frameworks like Apache Spark, Hadoop, Hive. Experience optimizing database performance, scalability, data security, and compliance. Experience with event-based, micro-batch, and batched high-volume, high-velocity transaction and More ❯
infrastructure-as-code (e.g., Terraform, CloudFormation), CI/CD pipelines, and monitoring (e.g., CloudWatch, Datadog). Familiarity with big data technologies like Apache Spark, Hadoop, or similar. ETL/ELT tools and creating common data sets across on-prem (IBMDatastage ETL) and cloud data stores Leadership & Strategy: Lead Data More ❯
engineer Proficiency in programming languages such as Python, Java, or Scala. Strong experience with relational databases (e.g., PostgreSQL, MySQL) and big data technologies (e.g., Hadoop, Spark). Experienced with Elasticsearch and Cloud Search. Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud Platform. Experience with More ❯
Service Catalogue, Cloud Formation, Lake Formation, SNS, SQS, Event Bridge Language & Scripting: Python and Spark ETL: DBT Good to Have: Airflow, Snowflake, Big Data (Hadoop), and Teradata Responsibilities: Serve as the primary point of contact for all AWS related data initiatives and projects. Responsible for leading a team of More ❯
security and compliance frameworks (e.g., NIST framework). Cloud certifications such as AWS Certified Developer, Oracle Cloud Infrastructure. Familiarity with big data technologies like Hadoop, Spark, and Kafka. Familiarity with records management standards (e.g., NARA standards). Clearance Requirements: Must have a current and active TS/SCI with More ❯
Experience in commodities markets or broader financial markets. Knowledge of quantitative modeling, risk management, or algorithmic trading. Familiarity with big data technologies like Kafka, Hadoop, Spark, or similar. Why Work With Us? Impactful Work: Directly influence the profitability of the business by building technology that drives trading decisions. Innovative More ❯
Experience in commodities markets or broader financial markets. Knowledge of quantitative modeling, risk management, or algorithmic trading. Familiarity with big data technologies like Kafka, Hadoop, Spark, or similar. Why Work With Us? Impactful Work: Directly influence the profitability of the business by building technology that drives trading decisions. Innovative More ❯
Account team within Services group (TTS) and is responsible for building a scalable, high-performance data platform on Big Data technologies (Spark, Scala, Hive, Hadoop) along with Kafka/Java and AI technologies to support core account data needs across multiple lines of businesses. As a tenant on the 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 ❯
architectures Proficiency in writing and optimizing SQL Knowledge of AWS services including S3, Redshift, EMR, Kinesis and RDS Experience with Open Source Data Technologies (Hadoop, Hive, Hbase, Pig, Spark, etc.) Ability to write code in Python, Ruby, Scala or other platform-related Big data technology Knowledge of professional software More ❯
