Sr Data Engineer

Day to day:
Insight Global is looking for a remote Data Engineer. Candidates will team up with the engineering teams and enterprise architecture (EA) to define standards, design patterns, accelerators, development practices, DevOps and CI/CD automation while creating and maintaining the data ingestion, quality testing and audit framework. Candidates will conduct complex data analysis to answer the queries from Business U or Technology team partners either directly from Analysts or stemmed from one of the Reporting tools such as PowerBI, Tableau, OBIEE and build and automate the data ingestion, transformation and aggregation pipelines using Azure Data Factory, Databricks / Spark, Snowflake, Kafka as well as Enterprise Scheduler tools such as CA Workload automation or Control M. Candidates will setup and evangelize the metadata driven approach to data pipelines to promote self-service and continuously improve the data quality and audit monitoring as well as alerting while constantly evaluate the process automation options and collaborate with engineering as well as architecture to review the proposed design.

Additional Responsibilities:
Demonstrate mastery of build and release engineering principles and methodologies including source control, branch management, build and smoke testing, archiving and retention practices
Adhere to and enhance and document the design principles, best practices by collaborating with Solution and in some cases Enterprise Architects
Participate in and support the Data Academy and Data Literacy program to train the Business U and Technology teams on Data
Respond SLA driven production data quality or pipeline issues
Document the Data Flow Diagrams, Data Models, Technical Data Mapping and Production Support Information for Data Pipelines

Pay Rate: $50-55/hr USD

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to .

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Required Skills & Experience

experience in an Enterprise Data Management or Data Engineering role
3+ of hands-on experience in building metadata driven data pipelines using Azure Data Factory, Databricks / Spark for Cloud Datalake
5+ years hands on experience with using one or more of the following for data analysis and wrangling Databricks, Python / PySpark, Jupyter Notebooks
Expert level SQL knowledge on databases such as but not limited to Snowflake, Netezza, Oracle, Sql Server, MySQL, Teradata
Experience working in a multi developer environment and hands on experience in using either azure devops or gitlab
Experience or strong understanding of the traditional enterprise ETL platforms such as IBM Datastage, Informatica, Pentaho, Ab Initio etc.

Nice to Have Skills & Experience

experience on one or more of big data technologies such as Cloudera Hadoop, Pivotal, Vertica, MapR
Functional knowledge of some of the following technologies - Terraform, Azure CLI, PowerShell, Containerization (Kubernetes, Docker)
Functional knowledge of one or more Reporting tools such as PowerBI, Tableau, OBIEE

Benefit packages for this role will start on the 31st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.