Senior Data Engineer

Walmart • Bentonville, AR

9d • $107,744 - $180,000 • Onsite

About The Position

What you'll do... Position: Senior Data Engineer Job Location: 1 Customer Drive, Bentonville, AR 72716 Duties: Data Strategy: understand, articulate, and apply principles of the defined strategy to routine business problems that involve a single function. Data Source Identification: support the understanding of the priority order of requirements and service level agreements. Helps identify the most suitable source for data that is fit for purpose. Performs initial data quality checks on extracted data. Data Transformation and Integration: extract data from identified databases. Creates data pipelines and transform data to a structure that is relevant to the problem by selecting appropriate techniques. Develops knowledge of current data science and analytics trends. Tech. Problem Formulation: translate/ co-own business problems within one's discipline to data related or mathematical solutions. Identifies appropriate methods/tools to be leveraged to provide a solution for the problem. Shares use cases and gives examples to demonstrate how the method would solve the business problem. Understanding Business Context: provide recommendations to business stakeholders to solve complex business issues. Develops business cases s for projects with a projected return on investment or cost savings. Translates business requirements into projects, activities, and tasks and aligns to overall business strategy and develops domain specific artifact. Serves as an interpreter and conduit to connect business needs with tangible solutions and results. Identify and recommend relevant business insights pertaining to their area of work. Data Modeling: analyze complex data elements, systems, data flows, dependencies, and relationships to contribute to conceptual, physical, and logical data models. Develops the Logical Data Model and Physical Data Models including data warehouse and data mart designs. Defines relational tables, primary and foreign keys, and stored procedures to create a data model structure. Evaluates existing data models and physical databases for variances and discrepancies. Develops efficient data flows. Analyzes data-related system integration challenges and proposes appropriate solutions. Creates training documentation and trains end-users on data modeling. Oversees the tasks of less experienced programmers and stipulates system troubleshooting supports. Code Development and Testing: write code to develop the required solution and application features by determining the appropriate programming language and leveraging business, technical, and data requirements. Creates test cases to review and validate the proposed solution design. Creates proofs of concept. Tests the code using the appropriate testing approach. Deploys software to production servers. Contributes code documentation, maintains playbooks, and provides timely progress updates. Data Governance: establish, modify, and document data governance projects and recommendations. Implements data governance practices in partnership with business stakeholders and peers. Interprets company and regulatory policies on data. Educates others on data governance processes, practices, policies, and guidelines. Provides recommendations on needed updates or inputs into data governance policies, practices or guidelines.

Requirements

• Master’s degree or the equivalent in Computer Science, Information Technology, Engineering, or a related field plus 1 year of experience in software engineering or related experience OR Bachelor's degree or the equivalent in Computer Science, Information Technology, Engineering, or a related field plus 3 years of experience in software engineering or related experience
• Must have experience with: developing highly scalable, distributed applications involving data ingestion, cleaning and transformation using Spark, Hive, Hadoop or HBase; publishing/consuming Kafka messages by enabling disaster recovery of topics with zero downtime; Data Lakehouse concepts and architecture leveraging open data formats like Parquet, AVRO, ORC and open table formats like Hudi, Apache Iceberg, DeltaLake; performing change data capture with incremental data loads using Apache Hudi; querying and monitoring logs using Graphana and Splunk; building and updating dashboards into Kibana by ingesting and transforming data from Logstash; coding in at least one Object Oriented language like Scala, Java, or Python; analyzing and managing data using a fully managed data warehouse like Big Query or Redshift; creating and deploying highly scalable clusters for batch and stream processing using DataProc; managing RESTful online file storage for storing and accessing data on GCS/Azure Blob Storage/S3 buckets; scheduling and automating data pipelines using Airflow/Atomic; performing source code version control with github/GitLab and developing CI/CD pipelines using Jenkins for code deployment; designing Helm Charts for fully functional and production ready spark apps and deployment using Argo CD gitops model; designing dashboards to deliver business insights using Looker/Tableau/Power BI; and implementing performance tuning of end-to-end applications for cost optimization.
• Employer will accept any amount of experience with the required skills.

Responsibilities

• Data Strategy: understand, articulate, and apply principles of the defined strategy to routine business problems that involve a single function.
• Data Source Identification: support the understanding of the priority order of requirements and service level agreements. Helps identify the most suitable source for data that is fit for purpose. Performs initial data quality checks on extracted data.
• Data Transformation and Integration: extract data from identified databases. Creates data pipelines and transform data to a structure that is relevant to the problem by selecting appropriate techniques. Develops knowledge of current data science and analytics trends.
• Tech. Problem Formulation: translate/ co-own business problems within one's discipline to data related or mathematical solutions. Identifies appropriate methods/tools to be leveraged to provide a solution for the problem. Shares use cases and gives examples to demonstrate how the method would solve the business problem.
• Understanding Business Context: provide recommendations to business stakeholders to solve complex business issues. Develops business cases s for projects with a projected return on investment or cost savings. Translates business requirements into projects, activities, and tasks and aligns to overall business strategy and develops domain specific artifact. Serves as an interpreter and conduit to connect business needs with tangible solutions and results. Identify and recommend relevant business insights pertaining to their area of work.
• Data Modeling: analyze complex data elements, systems, data flows, dependencies, and relationships to contribute to conceptual, physical, and logical data models. Develops the Logical Data Model and Physical Data Models including data warehouse and data mart designs. Defines relational tables, primary and foreign keys, and stored procedures to create a data model structure. Evaluates existing data models and physical databases for variances and discrepancies. Develops efficient data flows. Analyzes data-related system integration challenges and proposes appropriate solutions. Creates training documentation and trains end-users on data modeling. Oversees the tasks of less experienced programmers and stipulates system troubleshooting supports.
• Code Development and Testing: write code to develop the required solution and application features by determining the appropriate programming language and leveraging business, technical, and data requirements. Creates test cases to review and validate the proposed solution design. Creates proofs of concept. Tests the code using the appropriate testing approach. Deploys software to production servers. Contributes code documentation, maintains playbooks, and provides timely progress updates.
• Data Governance: establish, modify, and document data governance projects and recommendations. Implements data governance practices in partnership with business stakeholders and peers. Interprets company and regulatory policies on data. Educates others on data governance processes, practices, policies, and guidelines. Provides recommendations on needed updates or inputs into data governance policies, practices or guidelines.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 1-10 employees