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Database Management System: Storing, organizing, managing, and delivering data using relational DBs, NoSQL DBs, Graph DBs, and data warehouse technologies including AWS Redshift and Snowflake. Workflow Orchesration: Airflow, AppFlow, Austosys, Cloudwatch, Splunk.
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Bachelor’s degree in Computer Science, Engineering, IT, MIS, or a related disciplineExpertise in Python, SQL, and RExpertise in ingesting data from a variety of structures including relational databases, Hadoop/Spark, cloud data sources, XML, JSON Expertise in ETL concerning metadata management and data validation Expertise in Unix and Git Expertise in Automation tools (Autosys, Cron, Airflow, etc.
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Experience with AWS Services (i.e. S3, EMR, etc) a plus Experience with Cloud data warehouses, automation, and data pipelines (i.e. Snowflake, Redshift) a plus. Experience with AWS Services (i.e. S3, EMR, etc) a plus Experience with Cloud data warehouses, automation, and data pipelines (i.e. Snowflake, Redshift) a plus.
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Data warehouses: (Google BigQuery, AWS, Snowflake, etc.) Scheduling or orchestration: (dbt, Airflow, etc.) Data warehouses: (Google BigQuery, AWS, Snowflake, etc.) Scheduling or orchestration: (dbt, Airflow, etc.
$90,000 - $117,000 a yearExpandApply NowActive JobUpdated 3 days ago - UpvoteDownvoteShare Job
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Snowflake, IICS, Airflow, Control-M etc. WE VALUE Should have developed and deployed complex big data ingestion jobs in IICS (or other ELT tool) bringing prototypes to production on Snowflake (or any data warehouse platform.
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Data bases (SQL, NoSQL) and Data Platforms (Databricks, Snowflake) Strong skills with Database management, Data modeling and design DevOps and Security CI/CD, Serverless compute, OAuth, SSO, MFA etc.
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Good knowledge and experience in these technologies are required: AWS solution architecture designs and implementations Java / J2EE programming SOA and microservices Python programming language SQL / Database knowledge Kubernetes / Istio Apache Airflow / MWAA Apache Spark Terraform / Gitlab Basic UNIX experience and comfortable with bash Agile development methodology Excellent verbal, written and team communication skills.
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Graduate-level degree in computer science, engineering, or relevant work experience Preferred: Understanding of ML frameworks (sklearn, TensorFlow, PyTorch, etc) Experience working with big data platforms (Hadoop, Redshift, Snowflake, etc) Architecture, design patterns, production scaling/optimization Insurance industry experience Salary range: $132,500-$197,500 Overtime eligible: Exempt Discretionary bonus eligible: Yes Sales bonus eligible: No.
$132,500 - $197,500ExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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4+ years' experience with data orchestration workflow tools such as DBT, Airflow etc. 4+ years' experience working with big-data technologies/databases, e.g. Spark, Mongodb, Elastic search, Snowflake, Neo4j, etc.
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Tech stack includes Airflow, Spark, Databricks, Delta Lake, Snowflake, Scala, Python. Experience with at least one major Massively Parallel Processing (MPP) or cloud database technology (Snowflake, Redshift, Big Query.
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Experience with data warehouse solutions like Redshift, Snowflake, or BigQuery, and data orchestration tools such as Apache Airflow. Collaborate with data producers to understand data sources and contribute to the design and implementation of efficient data models using Redshift and Snowflake.
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Extensive experience using Snowflake, AWS SageMaker, GCP/GCP BigQuery, DBT, and Airflow for AI/ML model deployment and operationalization. This includes, but is not limited to, setting up SageMaker instances, creating Docker images, configuring lambda functions, setting up orchestration layer via Airflow, deploying endpoints, and creating API gateways.
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Use best practices to design and develop feature stores on Snowflake and other platforms to support rapid AI/ML model development. Familiarity with advanced statistical and machine learning techniques such as clustering, gradient boosting machines (GBM), support vector machines (SVM), neural networks (e.g., ANN, RNN, CNN), and other deep learning algorithms is a plus.
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Strong programming skills with one or more languages such as Python, PySpark, Apache Spark, Java, JavaSript, C, C. Job DetailsAbout SalesforceWe’re Salesforce, the Customer Company, inspiring the future of business with AI+ Data +CRM. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way.
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The Director, Data & ML Engineering willl be responsible for both data engineering and MLOps engineering teams to support data science applications. Oversee the entire lifecycle of data engineering projects: build scalable, reliable, and high performing data ingestion pipelines that collect, transform, integrate, and load structured, semi-structured, and unstructured data from a variety of sources, such as transactional data, data warehouse, and data lakes.
$185,800 - $269,500 a yearFull-timeExpandApply NowActive JobUpdated Today
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