recognizing the capabilities and limitations of each method Ability to categorize the data and metadata to build the metadata application profile. Experience with ApacheHadoop, HUE, Hive, Pig, Spark, Elasticsearch, Kibana, or Tableau Must be eligible to work in the United States and obtain and maintain an Active U.S More ❯
delivering projects with a commercial mindset. Prior experience with Event Sourcing (Kafka, Akka, Spark) and Data Distribution based architecture Experience with NoSQL (Mongo, Elastic, Hadoop), in memory (MEMSQL, Ignite) and relational (Sybase, DB2, SybaseIQ) data store solutions. Strong knowledge of data structures, algorithms, and design patterns Experience in data More ❯
Pig is highly desired • Experience with Data Science • Experience with Graphic Algorithms • Experience with Machine Learning • Experience with AWS • Cloud development experience such as Hadoop, Big Data (Cloudbase/Accumulo and Big Table) as well as JSON/BSON • Experience with analytic development • Experience with Python and streaming capabilities More ❯
with cross-functional teams, and play a key role in optimising their data infrastructure. Requirements: Strong experience in Python, SQL, and big data technologies (Hadoop, Spark, NoSQL) Hands-on experience with cloud platforms (AWS, GCP, Azure) Proficiency in data processing frameworks like PySpark A problem-solver who thrives in More ❯
with cross-functional teams, and play a key role in optimising their data infrastructure. Requirements: Strong experience in Python, SQL, and big data technologies (Hadoop, Spark, NoSQL) Hands-on experience with cloud platforms (AWS, GCP, Azure) Proficiency in data processing frameworks like PySpark A problem-solver who thrives in More ❯
with cross-functional teams, and play a key role in optimising their data infrastructure. Requirements: Strong experience in Python, SQL, and big data technologies (Hadoop, Spark, NoSQL) Hands-on experience with cloud platforms (AWS, GCP, Azure) Proficiency in data processing frameworks like PySpark A problem-solver who thrives in More ❯
Big Data infrastructure, ETL tools, data modeling, and computing platforms like AWS, Azure, and Google Cloud Strong command of SQL and experience working with Hadoop and Spark Bonus points if you have experience with Machine Learning Proactive team member who can communicate technical concepts to non-technical stakeholders Fluent More ❯
Engineering, Mathematics, or related field. - Proven experience (5+ years) in developing and deploying data engineering pipelines and products - Strong proficiency in Python - Experienced in Hadoop, Kafka or Spark - Experience leading/mentoring junior team members - Strong communication and interpersonal skills, with the ability to effectively communicate complex technical concepts More ❯
information with attention to detail and accuracy. Adept at queries, report writing, and presenting findings. Experience working with large datasets and distributed computing tools (Hadoop, Spark, etc.) Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, etc.). Experience with data profiling tools and processes. More ❯
information with attention to detail and accuracy. Adept at queries, report writing, and presenting findings. Experience working with large datasets and distributed computing tools (Hadoop, Spark, etc.) Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, etc.). Experience with data profiling tools and processes. More ❯
with source control tools (e.g., Git) and CI/CD pipelines. Desirable Skills Familiarity with big data or NoSQL technologies (e.g., MongoDB, Cosmos DB, Hadoop). Exposure to data analytics tools (Power BI, Tableau) or machine learning workflows. Knowledge of data governance, GDPR, and data compliance practices. Why Join More ❯
data governance. Cloud Computing : AWS, Azure, Google Cloud for scalable data solutions. API Strategy : Robust APIs for seamless data integration. Data Architecture : Finbourne LUSID, Hadoop, Spark, Snowflake for managing large volumes of investment data. Cybersecurity : Strong data security measures, including encryption and IAM. AI and Machine Learning : Predictive analytics More ❯
architecture, etc Cloud Computing : AWS, Azure, Google Cloud for scalable data solutions. API Strategy : Robust APIs for seamless data integration. Data Architecture : Finbourne LUSID, Hadoop, Spark, Snowflake for managing large volumes of investment data. Cybersecurity : Strong data security measures, including encryption and IAM. AI and Machine Learning : Predictive analytics More ❯
architecture, etc Cloud Computing : AWS, Azure, Google Cloud for scalable data solutions. API Strategy : Robust APIs for seamless data integration. Data Architecture : Finbourne LUSID, Hadoop, Spark, Snowflake for managing large volumes of investment data. Cybersecurity : Strong data security measures, including encryption and IAM. AI and Machine Learning : Predictive analytics More ❯
data governance. Cloud Computing : AWS, Azure, Google Cloud for scalable data solutions. API Strategy : Robust APIs for seamless data integration. Data Architecture : Finbourne LUSID, Hadoop, Spark, Snowflake for managing large volumes of investment data. Cybersecurity : Strong data security measures, including encryption and IAM. AI and Machine Learning : Predictive analytics More ❯
and data dictionaries Familiar with modern data visualisation tools (e.g. QuickSight, Tableau, Looker, QlikSense) Desirable Skills Exposure to large-scale data processing tools (Spark, Hadoop, MapReduce) Public sector experience Experience building APIs to serve data Familiarity with other public cloud platforms and data lakes AWS certifications (e.g. Solutions Architect More ❯
data analytics, software engineering, or related technical field. A minimum of five (5) years of hands-on experience with Big Data applications, such as Hadoop, and associated applications (e.g., administration, CM, monitoring, performance tuning, etc.) Desired: Experience working in a government mission Data Exploitation environment (e.g., acquiring data, storing More ❯
learn. Familiarity with cloud platforms like AWS, GCP, or Azure. Strong written and spoken English skills. Bonus Experience: Experience with big data tools (e.g., Hadoop, Spark) and distributed computing. Knowledge of NLP techniques and libraries. Familiarity with Docker, Kubernetes, and deploying machine learning models in production. Experience with visualization More ❯
Columbia, Maryland, United States Hybrid / WFH Options
SilverEdge
average 1-2 days per week. Flexibility is essential to adapt to schedule changes if needed. Desired Qualifications Experience with big data technologies like: Hadoop, Spark, MongoDB, ElasticSearch, Hive, Drill, Impala, Trino, Presto, etc. Experience with containers and Kubernetes are a plus Work could possibly require some on-call More ❯
the schedule. Preferred Requirements Prior experience or familiarity with DISA's Big Data Platform or other Big Data systems (e.g. Cloudera's Distribution of Hadoop, Hortonworks Data Platform, MapR, etc ) is a plus. Experience with CI/CD pipelines (e.g. Gitlab-CI, Travis-CI, etc.). Understanding of agile More ❯
work independently while also thriving in a collaborative team environment. Experience with GenAI/LLMs projects. Familiarity with distributed data/computing tools (e.g., Hadoop, Hive, Spark, MySQL). Background in financial services, including banking or risk management. Knowledge of capital markets and financial instruments, along with modelling expertise. More ❯
about business, product, and technical challenges in an enterprise environment - Extensive hands-on experience with data platform technologies, including at least three of: Spark, Hadoop ecosystem, orchestration frameworks, MPP databases, NoSQL, streaming technologies, data catalogs, BI and visualization tools - Proficiency in at least one programming language (e.g., Python, Java More ❯
level security clearance preferred. Prior experience or familiarity with DISA's Big Data Platform or other Big Data systems (e.g. Cloudera's Distribution of Hadoop, Hortonworks Data Platform, MapR, etc ) is a plus. Experience with Kubernetes (or vendor flavor of Kubernetes) Experience with CI/CD pipelines (e.g. Gitlab More ❯
DDL, MDX, HiveQL, SparkSQL, Scala) Experience with one or more scripting language (e.g., Python, KornShell) PREFERRED QUALIFICATIONS Experience with big data technologies such as: Hadoop, Hive, Spark, EMR Experience as a data engineer or related specialty (e.g., software engineer, business intelligence engineer, data scientist) with a track record of More ❯
