Reviewers say women are treated fairly and equally to men
What you'll do...
Data Strategy: Understands, articulates, and applies principles of the defined strategy to routine business problems that involve a single function.
Data Transformation and Integration: 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.
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 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
Code Development and Testing: 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.
Problem Formulation: Translates business problems within one's discipline to data related or mathematical solutions. Identifies what methods (for
example, analytics, big data analytics, automation) would provide a solution for the problem. Shares use cases and gives examples to demonstrate
how the method would solve the business problem.
Applied Business Acumen: 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. Serves as an interpreter and conduit to connect business needs with tangible solutions and results. Recommends new
processes and ways of working.
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
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.
Provides and supports the implementation of business solutions by building relationships and partnerships with key stakeholders; identifying business
needs; determining and carrying out necessary processes and practices; monitoring progress and results; recognizing and capitalizing on
improvement opportunities; and adapting to competing demands, organizational changes, and new responsibilities.
Models compliance with company policies and procedures and supports company mission, values, and standards of ethics and integrity by
incorporating these into the development and implementation of business plans; using the Open Door Policy; and demonstrating and assisting others
with how to apply these in executing business processes and practices.
Minimum of 5+ years of Big data development experience
Demonstrates up-to-date expertise in Data Engineering, complex data pipeline development
Experience in designing, developing and tuning distributed data processing pipelines that process large volume of data; focusing on scalability, low-latency, and fault-tolerance
Experience with Advanced Python (OOPS) to write data pipelines and data processing layers
Experience working on GCP (DataProc, Big Query) or equivalent cloud databases and Airflow for workflow orchestration
Strong Experience in Spark Scala
Demonstrates expertise in writing complex, highly-optimized queries across large data sets
Proven, working expertise with Big Data Technologies such as Hadoop, HDFS, Hive, Spark Scala/PySpark, Kafka, Apache Flink and SQL
Expertise in creating real time data streaming and processing pipelines using Kafka and/or Spark streaming, Flink etc.
Retail experience is huge plus
Option 1: Bachelor's degree in Computer Science and 3 years' experience in software engineering or related field. Option 2: 5 years' experience in
software engineering or related field. Option 3: Master's degree in Computer Science and 1 year's experience in software engineering or related
2 years' experience in data engineering, database engineering, business intelligence, or business analytics.
Data engineering, database engineering, business intelligence, or business analytics, ETL tools and working with large data sets in the cloud, Master's degree in Computer Science or related field and 3 years' experience in software engineering
350 N SAINT PAUL ST, DALLAS, TX 75201-4240, United States of America
Reviewers say women are treated fairly and equally to men