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<p style="margin-bottom:11px;font-family: Arial"><span style="font-size:11pt"><span style="line-height:107%"><span style="font-family:Calibri,sans-serif">At MSB, we believe in the value that data could bring to our businesses and our customers. We are transforming the bank into a data-driven organization by building the foundation, processes, and capability to democratize data to decision makers. To achieve this potential, we are looking for talented Analytics Engineers to join our journey. </span></span></span></p>
MSB’s Analytics Engineers sit at the intersection of business teams, Data Analytics, and IT and are responsible for bringing robust, efficient, and integrated data models to life. Analytics Engineers can speak the language of both business and technical teams, aiming to translate data insights and analysis needs into models powered by the MSB Data Platform. The successful Analytics Engineer is able to blend business acumen with technical expertise and transition between business strategy and data development.
Responsibilities
As a team member responsible for helping to bridge the gap between business and technology, the Analytics Engineer role requires equal amounts of business acumen and technical understanding.
- Collaborate with stakeholders, and team members to understand the analytics needs of the domain, define successful analytics outcomes, and fulfill those needs.
- Partner with IT functions to define requirements about data infra functions and data sourcing.
- Design, build, and deploy data models that support multiple analytics use cases across the bank.
- Contribute to data catalog, a resource to support a single source of truth analytics.
- Implement the DataOps philosophy in everything you do.
- Craft code that meets our internal standards for style, maintainability, and best practices for a high-scale database environment. Maintain and advocate for these standards through code review.
- Perform bug fixes, and apply enhancements to the models when the need arises
<div class="job_qualifications">
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<li style="margin-left:8px"><span style="font-size:11pt"><span style="line-height:107%"><span style="font-family:Calibri,sans-serif">Bachelor’s or Master’s degree in Statistics, Mathematics, Quantitative Analysis, Computer Science, Software Engineering, or Information Technology</span></span></span></li>
<li style="margin-left:8px"><span style="font-size:11pt"><span style="line-height:107%"><span style="font-family:Calibri,sans-serif">5+ years in the Data space as an analyst, engineer, or equivalent.</span></span></span></li>
<li style="margin-left:8px"><span style="font-size:11pt"><span style="line-height:107%"><span style="font-family:Calibri,sans-serif">Well-versed in SQL</span></span></span></li>
<li style="margin-left:8px"><span style="font-size:11pt"><span style="line-height:107%"><span style="font-family:Calibri,sans-serif">5+ years’ experience designing, implementing, operating, and extending commercial Kimball enterprise dimensional models.</span></span></span></li>
<li style="margin-left:8px"><span style="font-size:11pt"><span style="line-height:107%"><span style="font-family:Calibri,sans-serif">2+ years’ experience building reports and dashboards in a data visualization tool</span></span></span></li>
<li style="margin-left:8px"><span style="font-size:11pt"><span style="line-height:107%"><span style="font-family:Calibri,sans-serif">Positive and solution-oriented mindset</span></span></span></li>
<li style="margin-left:8px"><span style="font-size:11pt"><span style="line-height:107%"><span style="font-family:Calibri,sans-serif">Self-motivated and self-managing, with task organizational skills</span></span></span></li>
<li style="margin-left:8px"><span style="font-size:11pt"><span style="line-height:107%"><span style="font-family:Calibri,sans-serif">Great communication: Regularly achieve consensus amongst technical and business teams</span></span></span></li>
<li style="margin-bottom:11px; margin-left:8px"><span style="font-size:11pt"><span style="line-height:107%"><span style="font-family:Calibri,sans-serif">Comfortable with ambiguity, and able to thrive with minimal oversight and process</span></span></span></li>
Nice to have
Knowledge of banking industry
- Comfortable working with Git and the command line.
- Ability to write performant Python, PySpark, or Scala code.
- Experience working with modern data stack, including data orchestration tools (airflow, dragster, perfect), and data transformation (dbt).
- Hand-on experience in DevOps
- Knowledge of modern data platforms (Data Lake, Lakehouse, Data mesh).
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