"Alerted.org

Job Description

The primary responsibility of Senior Data Management Engineer is to build data pipelines, model and prepare data, perform complex data analysis to answer Business questions, build and automate data pipeline and quality framework to enable and promote self service data pipelines, assist in operationalizing the AI / ML Engineering solutions. This role is expected to lead and guide other team members and evangelize the design patterns as well as coding standards.

This role plays an active part in our Data Modernization project to migrate the from on-prem platforms such as IBM Netezza to cloud project

Responsibilities:

Team up with the engineering teams and enterprise architecture (EA) to define standards, design patterns, accelerators, development practices, DevOps and CI/CD automation

Create and maintain the data ingestion, quality testing and audit framework

Conduct complex data analysis to answer the queries from Business Users or Technology team partners either directly from Analysts or stemmed from one of the Reporting tools suchs PowerBI, Tableau, OBIEE.

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

Setup and evangelize the metadata driven approach to data pipelines to promote self service

Setup and continuously improve the data quality and audit monitoring as well as alerting

Constantly evaluate the process automation options and collaborate with engineering as well as architecture to review the proposed design.

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 Users and Technology teams on Data

Respond SLA driven production data quality or pipeline issues

Work in a fast-paced Agile/Scrum environment

Identify and assist with implementation of DevOps practices in support of fully automated deployments

Document the Data Flow Diagrams, Data Models, Technical Data Mapping and Production Support Information for Data Pipelines

Follow the Industry standard data security practices and evangelize the same across the team.

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 [email protected] learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.

Skills and Requirements

5+ years of 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

3+ years of hands on experience on one or more of big data technologies such as Cloudera Hadoop, Pivotal, Vertica, MapR is a plus

Experience working in a multi developer environment and hands on experience in using either azure devops or gitlab

Preferably experienced in SLA driven Production Data Pipeline or Quality support

Experience or strong understanding of the traditional enterprise ETL platforms such as IBM Datastage, Informatica, Pentaho, Ab Initio etc.

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

Team player with excellent communication skills, ability to communicate with the customer directly and able to explain the status of the deliverables in scrum calls

Ability to implement Agile methodologies and work in an Agile DevOps environment Bachelor’s degree in Computer Science or Engineering or Mathematics or related field and 5+ years of experience in various cloud technologies within a large-scale organization

Personal Attributes: Self-starter, Collaborative, Curious, Strong work ethic, highly motivated, Team oriented

Experience designing and building complex data pipelines in an agile environment

Expertise on data analysis and wrangling using sql, python, databricks

Experience with modern cloud development and design concepts; software development lifecycle; multi-developer code versioning and conflict resolution; planning, design, and problem resolution enterprise data applications / solutions

Demonstrated ability in developing a culture that embraces innovation, and challenges existing paradigms