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Experience with Data Management methodologies and practices such as data warehousing, data integration (ETL/ELT), visualizations, metadata management, data security, data governance, data quality and analytics.
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ETL tools Teradata, MS SQL Server, Data Transformation Services, Oracle SQL Developer, SQL Server Integration Service (SSIS), ADF, DataStage, Azure Synapse. Strong preference will be given to candidates with knowledge of: MS SQL Management Studio MS SQL Server MariaDB SolarWinds DPA Index Tuning E-R Diagramming Data Normalization Backup and Restore Clustered Databases Query Optimization MongoDB PostgreSQL Oracle Intersystem IRIS Database Tools: SQL Server Management Studio, Azure Data Studio, SQL Profiler, SQL Prompt.
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Leading team in the definition of best practices & repeatable methodologies in Cloud Data Engineering, including Data Storage, ETL, Data Integration & Migration, Data Warehousing and Data Governance.
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Data integration & engineering using modern enterprise development toolsets ( ETL, ELT, MDM, Quality, CDC, Data Masking)Responsible for cloud data integration architecture, development, testing, data quality, and on-going auditing.
$60.19 - $96.31 an hourFull-timeRemoteExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Designs, develops, and implements ETL/ELT processes using Azure Data Factory, Synapse pipelines, Databricks Notebooks, Event Hub to build integrations from Saas sources such as Service Now, Workday, Dynamics CRM, and Eloqua.
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5 years of experience in integration design and operationalization (REST APIs, Kafka, Golden Gate, ETL, Snowflake) Partner with Regulatory and Technology stakeholders to deliver and maintain architecture artifacts, including tactical and strategic product roadmaps, data flow diagrams, reference architecture diagrams, process and journey maps, integration diagrams, data and content architecture artifacts, software engineering artifacts and security architecture diagrams.
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Minimum 3 years' experience working with Cloud technologies such as Synapse pipelines, Azure Data Factory (ADF), ADLS, Azure Databricks, Spark, Azure Synapse, and other modern data ETL/ELT technologies.
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KEY QUALIFICATIONS: Python, SQL Data processing, ML experience Data Warehouse knowledge ETL pipeline knowledge Data Engineering Data Science Data Analytics, Data Mining PLEASE HAVE KNOWLEDGE OF ONE OR MORE OF THE FOLLOWING TECHNICAL SKILLS: Kubernetes, Tableau, PowerBi MongoDB Microsoft Cloud Services like Azure and AKS Snowflake SQL Server data platform Software development (including design, implementation, testing, and change management.
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Experience with data integration, ETL, and data visualization tools. Experience with Databricks, Alteryx, Data integration, Data Masking tools, Access Management and Data Governance tools.
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Responsibilities Data Integration and Pipeline Development: Design and build scalable data pipelines using tools like Fivetran, dbt Cloud, Python, PySpark, and Airflow to integrate data from diverse sources including Sales, Finance, Planning, Manufacturing, and Factory applications into a Snowflake data warehouse.
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Experience working with Integration Technologies such as MuleSoft,Jitterbit,Boomi, Informatica, Talend,Snaplogic, Salesforce APIs, APEX,and other similar ETL tools. Ability to build mock Proof of Concepts for Data Integration with Salesforce, Anaplan, Workday, NetSuite, SQL/Oracle DB, Snowflakeand a variety of Cloud-basedBusiness Systems for potential clients.
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Working experience using Data Pipeline (ELT or ETL) tools such as Talend, NiFi, dBt, DataStage, or ADE. Hands-on expertise of multiple modern storages and services such as Snowflake, Azure SQL, ADLS2, Azure Cosmos DB, Databricks, MongoDB, CockroachDB, DataStax, Oracle, Sybase, DB2, or Redis.
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Experience working with or general knowledge of Big Data or NoSQL database system (DynamoDB, MongoDB, Redshift, BigQuery, Azureetc) a plus. Implementation of other data related activities such as standardized automated ETL processes, reports, dashboards, models, etc.
$70,000 - $110,000 a yearExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Experience with NoSQL databases such as mongoDB, Cassandra or similar is a plusMinimum of 4 years of experience in developing data ingestion, data processing and analytical pipelines for big data, relational databases, NoSQL, data lake and data warehouse solutionsMinimum of 4 years of hands-on experience in Big Data technologies such as, PySpark, Spark/SparkSQL, Dask or similar distributed compute frameworks.
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At least 6+ years of data engineering experience including data management, analysis, design and integration/ETL. Prior experience of Insurance domain a huge plusStrong knowledge of MDM technology, SQL and advanced programming languages such as Python/JavaHands-on experience with MDM tools and Cloud services.
$101,000 - $172,000Full-timeExpandApply NowActive JobUpdated Today
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