Data Solutions Specialist

JOB CLASSIFICATION

Full / Part-time: Full-time

Hours Per Week: 40

Location: 1785 E Ruben M Torres Sr Blvd Brownsville, Texas 78521

JOB SUMMARY

Data Solutions Specialist works with a data team to build dataset representations and tools. The specialist aims to create datasets that allow the end-user to understand and evaluate the information provided within the data. They use a combination of business strategy and technical data knowledge to translate complex information into clear and helpful visual representations known as data models.

Data Solutions Specialist works with data analysts and data engineers to aid building and deploying a highly performant data platform that is able to support analytics-related initiatives across the enterprise. This person is a key contributor on data initiatives through the delivery of data pipelines, reports, dashboards, and insights derived from business intelligence assets. They ensure data sourced for pipelines, reports, and dashboards they deliver are from quality data sources while also supporting data preparation requirements for analytics team members.

ESSENTIAL DUTIES

The duties listed below may not include all responsibilities that the person in this role may be asked to perform. Incumbent may be required to perform other related duties as assigned.

1. A subject matter expert on the bank's enterprise data architecture

2. Provides support for the bank's analytics and data-driven initiatives.

3. Manipulates, maps, and integrates data from existing data products, pipelines, and reports to support data value delivery.

4. Performs ad hoc data quality checks on pipeline data to support data quality management and issue remediation processes.

5. Provides requirements to Data Architect to support data design requirements for strategic data assets.

6. Ensures data integration efforts supporting business requirements conform to established Enterprise and domain data models, as required.

7. Translates engineering and technical concepts to senior management and non-technical employees to enable understanding and drive informed business decisions.

8. Maintains communication with Data Product Management Leadership, internal stakeholders, and other lines of business to ensure that there is visibility into the Product's direction, schedule, progress, and operational status.

9. Creating and maintaining documentation that includes the design, requirements, and user manuals for the organization.

10. Support data quality initiatives by contributing to the development of data quality rules, standards, and processes.

11. Develop and maintain procedures for data validation and cleansing to ensure accuracy and quality of data as it relates to data governance, data management, and data architecture.

12. Performs data discovery across the entire enterprise to consolidate large amounts of data into a single unified platform.

13. Coordinate with the IT security team to develop and enforce policies for data access and authentication.

14. Strong individual planning and project management skills, able to juggle multiple tasks and priorities.

15. Support Analytics and Insights team by providing the necessary data sets and tools for analysis .

16. Continue to evolve and improve technical skills with SQL, Python, Spark, and other emerging data management technologies.

17. Full ownership of the model development process and relationship with the business customer from conceptualization through data exploration, model selection and validation, implementation, business user training and support.

18. Leads efforts to develop scalable, efficient, automated solutions for large scale data analyses, model development, model validation and model implementation.

Requirements

QUALIFICATIONS

These specifications are general guidelines based on the minimum experience normally considered essential to the satisfactory performance of this position. The requirements listed below are representative of the knowledge, skill and/or ability required to perform the position in a satisfactory manner. Individual abilities may result in some deviation from these guidelines.

1. Bachelor's degree in computer science, mathematics, statistics, economics, or other quantitative discipline OR 3+ of related experience beyond the minimum required may be substituted in lieu of a degree.

2. Data modeling experience to generate accurate models and communicate effectively through visual representations.

3. Ability to translate business requirements into database models, data processing pipelines, application programming interfaces (API), and data tooling.

4. Experience with Python and/or SQL is required (Pandas, PySpark, Dataframes, and similar libraries)

5. Understanding of data warehousing technologies such as Azure SQL Data Warehouse, Snowflake, BigQuery, or Redshift

6. Experience with schema design and dimensional data modeling

7. Excellent knowledge of relational databases such as Microsoft SQL Server, MySQL, PostgresSQL, or NoSQL

8. Strong written, oral, and presentation communication skills with the ability to shape messages and content to audiences of widely varying roles and technical backgrounds

PREFERRED SKILLS

Experience designing large data models and data marts for in production use in organization.

Experience working in regulated environments (e.g., Financial Services).

Preferred Experience with any of the following cloud data and analytics technologies:

o

Azure - Azure Databricks, Azure Data Lake, Event Hubs, SQL Data Warehouse, Azure Data Factory

o AWS - Elastic Map Reduce, Athena, Redshift, Kinesis, Glue, S3

o GCP - BigQuery, BigTable, Dataflow, DataProc, Google Cloud Storage

Machine Learning experience with either Azure ML, Spark Mllib, TensorFlow, or similar

Experience with Jupyter Notebooks

EOE/M/F/D/V
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