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Proficiency in data engineering concepts, tools, and technologies, with hands-on experience with Databricks or similar platforms. Manage and support the Data Engineering team responsible for leveraging Databricks for data processing, analytics, and machine learning.
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This role will perform hands-on delivery of solutions that include artificial intelligence (AI) and cognitive services, ML models, pipelines, databases, and other data analytics components, contributing to the development and unit testing of solutions.
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Job Title: Hands-On Engineering Manager Location: Newton, MA About Us: My client is a rapidly growing eCommerce beverage distribution company that achieved $200 million in revenue last They are at the forefront of revolutionizing the beverage industry by providing exceptional service and innovative solutions.
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Prior hands-on experience with data platforms and technologies such as Delta Lake, Spark, Kubernetes, Kafka, ClickHouse, and/or Presto/Trino. The Akuna Data Engineering team plays a crucial role in ensuring that trustworthy data is available, reliable, and accessible to support various data-driven initiatives within Akuna’s Quant, Trading, and Business Operations business units.
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Whether you’re telling a data story in ways our clients never imagined or building advanced AI models with automated data engineering, the core purpose will be centered on using data to impact people in a meaningful way.
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Minimum of 5 years of hands-on skills in Python, Apache Spark, Hive, Cassandra, Snowflake, Elastic, Lucene, DataBricks, Hadoop, Redshift, Scala, Java, or other relevant technologies in data engineering.
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Hands on development in Python, PL/SQL, SQL, Shell Scripting, AutoSys. Hands on experience working in cloud data platforms such as AWS Redshift, Spark based data engineering solutions.
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Experience in developing an end-to-end AWS native platform for building Data lakes (S3, Glue (Crawlers, ETL, Catalog), IAM, CodePipeline, CodeCommit, CloudFormation/Terraform, CloudTrail, CloudWatch, AWS Config, Guard Duty, Secrets Manager, KMS, EC2, Data Visualization Tool: Tableau run on an EC2 or AWS Quicksight), Athena, AWS AI (Bedrock, SageMaker, Q.
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Net, C#, Qlik, Power BI, Machine Learning, Azure Data Factory, RedShift, UiPath, Cloud, RPA, AWS, Redshift, Kinesis, QuickSight, SageMaker, S3, Databricks, AWS Lake Formation, Snowflake, Python, Qlik, Athena, Data Pipeline, Glue, Star Schema, Data Modeling, Performance Tuning, SQL Individual salaries that are offered to a candidate are determined after consideration of numerous factors including but not limited to the candidate’s qualifications, experience, skills, and geography.
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Must have hands on Snowflake, AWS and Airflow. 5+ years in data engineering with detailed knowledge of data warehouse technical architectures , infrastructure components , ETL ELT.
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Demonstrated experience building data pipelines with PySpark and AWS.Application development experience in financial services with hands on designing, developing, and deploying complex applications.
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More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow.
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Hands on experience in data engineering desired with extensive knowledge of SQL and PySpark, on Databricks Platform. Hands on experience designing, building, and optimizing data pipelines, architecture for large scale data warehousing projects.
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Hands-on experience with data warehousing, data lakes, and analytics platforms (e.g., Snowflake, Redshift, BigQuery). If you are passionate about leveraging data to drive meaningful insights and have a proven track record in data engineering, analytics, and leadership we invite you to join us on this exciting journey.
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Required 10 Years Hands-on experience with Azure services such as Azure Data Factory, Azure Databricks, Azure Data Lake Storage, Azure SQL, Azure Synapse Required 5 Years Hands-on experience in SQL Server (SSIS, SSRS, SSAS), ORACLE, T-SQL Required 10 Years Hands-on experience in Azure SQL Database, Azure SQL Datawarehouse Required 7 Years Hands-on experience in deploying and maintaining large-scale data processing pipelines.
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hands on data engineering jobs Company: Bdo in Beltsville, District Of Columbia
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