Big Data Expertise : 3+ years of hands-on experience with major Big Data technologies and frameworks, including Spark, Hive, ZooKeeper, HDFS, Presto, Hadoop, MapReduce, Tensorflow, and more.

Implement cutting-edge AI/ML techniques, including Generative AI, to boost the efficiency of the platform and data engineering processes. We are looking for a passionate Principal Engineering to help architect and scale the global data platform systems and services for our new global streaming app, Max, as well as any streaming and non-streaming initiatives within the company.

The big data architect will support the development of autonomous driving software solutions by playing the role of subject matter expert for the big data systems, underlying data and data products.

Comfortability with data warehouses and big data technologies such as Redshift, Snowflake, Big Query, Presto, Athena, Spark, DBT. Remote Data Scientist. The ideal candidate will be adept in navigating the data stack and able to support initiatives in all facets from analytics/data engineering and product analytics to machine learning.

Apply your skills with Databricks, using Python, spark, pyspark, and big data streaming to pioneer client technologies and data. Experience with large-scale distributed computing and big data technologies (databricks etc.

Advanced Analytics - Applied Econometrics, Advanced Calculus, Statistical Methods, Data Visualization, Decision Analytics & Optimization, ML, Big Data, Social Network Analytics. Techniques: Statistical Analysis, Visualization, Optimization, Machine Learning, Big Data, Data Warehouse, NLP.

Experience with some of the following: Kubernetes, Docker, Helm Charts, Hadoop, Cloudera, Hortonworks, Apache Storm, Apache Spark, HBase, YARN, map-reduce, big-data analytics, semantic-web (RDF, OWL), Hive, Elastic Search, MS SQL Server Big Data, and graph-databases.

The candidate should have expertise in data modeling, SQL, Python, R, data warehousing, big data technologies, data pipeline construction, data quality, cleansing, version control, cloud services, machine learning, feature engineering, deep learning, and natural language processing.

Certificate in business analytics, data mining, or statistical analysis, Statistical programming languages (for example, SAS, R) Drive the adoption of data science-driven mechanisms and machine learning models to continuously evaluate and improve catalog data quality.

Ensure the continuous improvement of data quality and completeness across Walmart's omni-business. Accurate and timely market data is critical to protecting our "Save Money, Live Better" promise, operating at low cost, and helping customers make purchase decisions.

As a big data engineer at Booz Allen, you’ll implement data engineering activities on some of the most mission-driven projects in the industry. We need an experienced data engineer like you to help our clients find answers in their big data to impact important missions—from fraud detection to cancer research to national intelligence.

In-depth knowledge of the Databricks Unified Analytics Platform and its features for collaborative big data analytics. Use of tools like Apache Airflow, ADF, or Databricks to orchestrate and schedule data workflows.

Expertise in Cloudera Big Data Technologies, including Cloudera Distribution of Hadoop (CDP), Apache Hadoop, Apache Spark, Apache Hive, Apache Impala, and Apache HBase, with hands-on experience in deploying, configuring, and optimizing these technologies for large-scale data processing and analytics.

The successful candidate will teach introductory and upper-level courses in Data Science such as Data Curation, Data Modeling, Data Management, Data Mining, Big Data, Data Analysis, Machine Learning, Data Visualization, Computational Thinking for Problem Solving, Information and Data Security and Privacy, Information and Data Quality, Information Retrieval, and Data Science courses in the candidate's area of expertise.

Experience with Big Data Technologies (NoSQL databases, Hadoop, Spark, Elasticsearch, Databricks, etc.) Experience in architecting data pipelines and solutions for streaming and batch integrations using tools/frameworks like dbt, Talend, Azure Data Factory, Spark, Spark Streaming, etc.