Senior Data Engineer

Walmart•Bentonville, AR

12d•$90,000 - $180,000•Onsite

About The Position

The Senior Data Engineer will identify possible options to address business problems through analytics, big data analytics, and automation. This role supports the development of business cases and recommendations, owns the delivery of project activities, and supports process updates and changes. The Senior Data Engineer will solve business issues, support the documentation and implementation of data governance processes, and understand and apply strategic principles to routine business problems. Key responsibilities include extracting data, creating data pipelines, transforming data, developing knowledge of current data science and analytics trends, and understanding requirement priorities and service level agreements. The role involves identifying suitable data sources, performing initial data quality checks, analyzing complex data elements, and developing logical and physical data models, including data warehouse and data mart designs. This includes defining relational tables, primary and foreign keys, and stored procedures, as well as evaluating existing data models and databases. The Senior Data Engineer will develop efficient data flows, analyze data-related system integration challenges, create training documentation, and train end-users on data modeling. Additionally, the role involves overseeing less experienced programmers, providing system troubleshooting support, writing code to develop solutions and application features, creating and testing code, deploying software to production, contributing code documentation, maintaining playbooks, and providing progress updates. The Senior Data Engineer will demonstrate up-to-date expertise, provide expert advice, align efforts to meet business needs, and build commitment for perspectives.

Requirements

Master’s degree or the equivalent in Computer Science or related field plus 1 year of experience in software engineering or a related field; OR Bachelor’s degree or the equivalent in Computer Science or related field plus 3 years of experience in software engineering or a related field.
Coding in an object-oriented programming language (Python, Scala or Java)
Shell scripting using UNIX/LINUX platforms
Designing and developing ETL data pipelines with big data processing frameworks (Spark, Hadoop, AWS EMR, AWS EC2, AWS S3, AWS Redshift, Azure Data Bricks, Azure Blob Storage, Azure Data Factory, GCP Data Proc)
Automating job scheduling using a workflow management platform (Automic, Airflow, Azure Data Factory)
Implementing and optimizing Spark applications and related components including Spark Core Engine, Spark SQL, Spark Streaming, MLlib
Data warehouse such as Snowflake, Redshift, Google Big Query
Developing applications using Apache Kafka, Confluent Kafka and Google Pub/Sub streaming processing frameworks
Building interactive dashboards using latest data visualization technologies like Tableau, Power BI, Google Data Studio
Relational Database Management Systems (MySQL, PostgreSQL, JDBC)
CICD automation using Jenkins, GitHub actions
Agile and Waterfall methodologies for project management

Responsibilities

Identifies possible options to address the business problems within one's discipline through analytics, big data analytics, and automation.
Supports the development of business cases and recommendations.
Owns delivery of project activity and tasks assigned by others.
Supports process updates and changes.
Solves business issues.
Supports the documentation of data governance processes.
Supports the implementation of data governance practices.
Understands, articulates, and applies principles of the defined strategy to routine business problems that involve a single function.
Extracts 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.
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.
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.
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.
Demonstrates up-to-date expertise and applies this to the development, execution, and improvement of action plans by providing expert advice and guidance to others in the application of information and best practices; supporting and aligning efforts to meet customer and business needs; and building commitment for perspectives and rationales.