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QTS Data Centers is a Blackstone REIT Portfolio companyQTS Data Centers is seeking a DCIM Engineer II / Controls Engineer II (Senior Data Center Infrastructure Management (DCIM) Engineer) to be based at one of our brand new mega data center campuses in the US. Quality Technology Services (QTS) is a leading provider of data center solutions across a diverse footprint spanning more than 9 million square feet of QTS Mega Data Centers throughout North America and Europe.
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Experience delivering solutions and insights on the Microsoft Azure platform with exposure to Azure Databricks, Azure Synapse, Azure Data Factory, PostgreSQL, Azure SQL DB, Power BI or Azure ADLS Gen2.
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Professional Certification such as Certified Analytics Professional (CAP), Databricks Data Engineer, Databricks Client Engineer, Azure Data Scientist Associate, DASCA s Senior or Principal Data Scientist Certification etc.
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Expertise in some of the following leading data and analytics technology stacks, such as Azure (ADF, Functions, Event Hub/Grid, Streaming, Synapse), AWS (Kinesis, Firehouse, Glue) Snowflake, DBT, Databricks, Informatica, DBT, Denodo.
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Interface with internal data center operations team, data center design engineering team, server hardware team, environmental health and safety team to promote standards that maintain consistency and reliability in services delivered.
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The Data Center Construction Manager will be responsible for construction project management and oversight of construction related activities as they relate to new builds or general capital projects which includes the ownership of the project scope, quality, schedule, and budget.
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Experience in the design and implementation of modern data architectures and concepts such as cloud services (AWS, Azure, GCP) and modern data warehouse tools (Snowflake, Databricks, Synapse, Redshift.
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ExposureMinimum 5+ years of experience Worked on large Data Engineering initiatives from start to finishFormal ETL tooling (Informatica, DataStage, etc.) Azure experience (not just a “cloud engineer” or just using services but more on data / migration side and creating pipelines etc.
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Required and Desired Skills/Certifications: Proven experience developing and maintaining data pipelines and ETL jobs using IBM DataStage, Informatica, Matillion, FiveTran, Talend or Dbt Knowledge of AWS cloud services such as S3, EMR, Lambda, Glue, Sage Maker, Redshift & Athena and/or Snowflake.
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Design and implement automated solutions for data normalization and taxonomy management using tools such as Python, R, SQL, and automation platforms. About the role: Gen3 is currently seeking a talented Data Scientist to join our team, dedicated to supporting the Internal Revenue Service (IRS) on the ISSM Vulnerability Compliance and Remediation Program.
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Familiarity with a Modern Data Stack (I.e., ETL tools like dbt, Airflow, Fivetran, and cloud data warehouses like BigQuery, Snowflake, Azure, or Redshift). Reporting to the CFO, you will own the entire business intelligence function: you will be the expert on company data and use that knowledge to answer questions, provide insight, and improve the business.
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Your expertise in ETL, DataBricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupiter Notebooks will be essential in ensuring efficient data processing and analysis. Job Responsibilities:- Design, develop, and implement end-to-end data pipelines, utilizing ETL processes and technologies such as DataBricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupyter Notebooks.
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Strong technical proficiency to contribute to data engineering task in an AWS and Databricks ecosystem. You must be passionate about data management with a solid background in AWS, Databricks, Python, Trino/Starburst, Databases and SQL.Design, develop, monitor, and maintain data pipelines in an AWS Gov Cloud ecosystem with AWS, Databricks, Delta Lake and Trino as the underlying platforms.
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You will leverage your expertise in ETL, Databricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupyter Notebooks to ensure efficient data processing and analysis. Design, develop, and implement end-to-end data pipelines, utilizing ETL processes and technologies such as Databricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupyter Notebooks.
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This position will also be responsible for developing and recommending a comprehensive maternal health data set to track progress, determining and establishing the mechanisms needed to establish the dashboard.
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data job Title: associate Company: Stanford Medicine
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