Position: Senior Data Engineer

Job Location: 811 Excellence Dr, Bentonville, AR 72716

Duties: Data Strategy: Understands, articulates, and applies principles of the defined strategy to routine business problems that involve a single function. Data Source Identification: Supports 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: Extracts data from identified databases. Creates data pipelines and transforms 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: Translates/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: Provides recommendations to business stakeholders to solve complex business issues. Develops business cases 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. Identifies and recommend relevant business insights pertaining to their area of work. Data Modeling: Analyzes 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 Requires: Writes 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: Establishes, modifies, and documents 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.

Minimum education and experience required: Bachelor's degree or the equivalent in Computer Science or related field plus 3 years of experience in software engineering or related experience; OR Master's degree or the equivalent in Computer Science or related field plus 1 year of experience in software engineering or related experience.

Skills Required: Must have experience with: Building scalable Scala-Spark pipelines connecting RDBMS and Hive sources to GCP BigQuery using Dataproc clusters with Airflow orchestration to solve data analytics requirements; Designing data models and ETL pipelines using PySpark to support enterprise-level analytics requirements; Implemented data quality frameworks in Scala or PySpark with Data Plex integration and Collibra governance tools; Leading migration of on-premise data processing to cloud infrastructure with performance optimization to meet SLA requirements; Architecting near real-time Kafka-based pipelines for member screening and Risk Tech or AML dashboards; Designing and implementing ETL pipelines in DataStage and creating UNIX script for ETL flow; Redesigning and optimizing SQL queries for Hadoop and Orchestrating workflow in Oozie; Developing NLP and LLM-based machine learning models to automate ECCN and HTS code classification for exported items to support U.S. export filing requirements; Migrating analytics workflows from Greenplum to Hadoop with Spark; Building ETL pipelines and batch processes in DataStage for RDBMS data loading; Preparing and executing unit tests, troubleshooting defects, and ensuring system functionality; Designing ETL workflows across DataStage, Hadoop-Oozie, and Teradata environments with UNIX scripting; DataStage migration, including code review and production deployment; Developing BTEQ scripts for loading data into Teradata tables. Employer will accept any amount of experience with the required skills.

Rate of pay: $94,557.00 - 180,000.00/year