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Experience working with big data technologies (e.g., Hadoop, Spark, and Hive) as well as ETL tools (e.g., Apache Nifi, Talend, Apache Airflow) and real-time data processing technologies such as Apache Kafka are essential.
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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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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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Utilize SQL Server Integration Services (SSIS) and Azure Data Factory for ETL processes and data migration. Experience with data integration techniques and tools such as SSIS and Azure Data Factory.
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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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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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3+ years of experience with data orchestration/ETL tools (Airflow, Nifi), preferred. Design table structures and define ETL pipelines to build performant Data solutions that are reliable and scalable in a fast growing data ecosystem.
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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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Strong knowledge of various database technologies (SQL, NoSQL), data integration (ETL/ELT application integration) frameworks, and cloud services (AWS, Azure, GCP). Key outputs include alignment of the data platform architecture, platform design, data modeling, data integration design, standards documentation, architecture to support partner solutions, and performance aligned with the overall goals and objectives for Apptio’s business and vision.
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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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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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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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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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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.
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Manage data transitions and platform migrations between SAP HANA/DataBricks, Tableau/PowerBI, and related ETL processes. Proficient in data platforms/systems (such as SQL, Databricks), ETL tools (such as Python, SnapLogic), process automation, and standardization.
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