PDI Technologies

Retail payment, loyalty, shopper insights

Data Engineer 3

Data EngineeringPosted on Nov 10

Full-timeNo salary listedIn-person

About the Job

Requirements

At least 7 years of experience in data engineering, data modeling, SQL, ETL, big databases, data warehousing, and basic administration of data infrastructure.
At least 7 years of coding experience in Java, Python, R, or an equivalent programming language.
At least 4 years of big data experience.
At least 2 years of experience as a technical lead architecting data lake, data warehouse, or lakehouse systems and mentoring data engineers or database administrators.
Proficiency with big-data tools and technologies, including Hadoop and Spark; storage formats such as Parquet, Delta, Apache Hudi, and Apache Iceberg; OLTP systems; and data ingestion mechanisms.
Experience building large-scale data lakes and warehouse systems in cloud environments, including AWS technologies such as S3, Redshift, Aurora/RDS, DMS, EC2, Glue Spark, CloudWatch, and EMR.
Experience with data orchestration tools such as Airflow.
Experience building pipelines and ingesting data from heterogeneous systems into data lake environments in real time.
Proficiency in Python, SQL, PL/SQL, query tuning, optimization, ETL, ELT, and data warehousing.
Proficiency in business intelligence and analytic databases and products, including translating business requirements into database tables, pipeline designs, and tasks.
Knowledge of data-specific concepts, frameworks, and processes; Agile development practices; and the software development life cycle.
Experience designing data warehouses, including their definition, structure, documentation, maintenance, long-range requirements, operational guidelines, and protection.
Knowledge of data governance, metadata management, data security measures, retention, and archival across data lake layers.
Experience with cloud platforms such as AWS, GCP, or Azure.
Experience building or managing data lake and lakehouse architectures and working with different data lake storage formats.
Ability to communicate effectively orally and in writing, multitask, manage multiple priorities, and work collaboratively in a team-oriented environment with people from different disciplines and technical backgrounds.
Experience working in an Agile team environment.

Responsibilities

Use architectural and design skills for a variety of data-oriented tasks.
Establish and maintain strong relationships with business stakeholders.
Build reliable and scalable data systems with data governance that provide complete, secure, accurate, and timely data for analytics.
Apply data and dimensional modeling expertise and business acumen to support new product features and services, including financial reporting.
Assist the development and analytics organization in meeting delivery goals related to data design, flow, and infrastructure.
Perform data modeling and big-data architecture design, support, and implementation for OLTP and real-time OLAP/data warehouse systems and ETL pipelines.
Track, build, and monitor data and system KPIs, including storage, performance, and usage.
Administer big-data databases and compute engines such as Redshift, EMR, and Spark, and apply optimization and tuning techniques.
Prepare documentation according to departmental standards.
Identify, analyze, and trace data problems as needed.
Recommend application and system improvements.
Mentor other team members.
Work with business users to understand business requirements, issues, and business or client processes.
Develop, test, and maintain high-performance data systems that meet business and client requirements and adhere to departmental standards.
Perform quality-assurance testing for all work performed.
Meet with Agile teams as required to define and document application requirements.
Follow project development and deployment processes and maintain industry standards and best coding practices.
Maintain the security and organization of company data.
Provide off-hours support as assigned.
Gather business requirements and features, estimate tasks, and design and develop scalable solutions.
Work with the manager to determine the company’s data requirements.
Plan work to meet project deadlines, accommodate development-team demands, set priorities, and escalate issues appropriately.
Recommend data restructuring and complex maintenance approaches to development teams.
Deploy and manage changes in development, staging, and production environments.
Assist development and DevOps teams with SQL queries and tuning.

For nearly 40 years, PDI has helped convenience retailers and petroleum wholesalers adapt to changes in the industry by leveraging the latest technologies. Simplifying the complexity in your world is our main focus. That's why we're delivering an integrated portfolio of global, cloud-based solutions and services to meet our customers needs today and well into the future. From the back office to fuel logistics, and the latest wave of consumer demands and digital commerce, PDI solutions and services are designed to give you a competitive edge. Our deep domain knowledge is backed by our industry-specific software offerings and a people-first approach. Serving the entire supply chain means that we’ve had to solve a wide range of industry challenges and deliver measurable value. To address the increasingly dynamic convenience retail and petroleum wholesale industry, PDI leads the way with converged digital, cloud-optimized, secure, and scalable solutions including ERP, Loyalty, Fuel Pricing, Point-of-Sale and Logistics to create a broader industry ecosystem. The result is unparalleled insights, simplified operations, and higher profitability for your employees and business. We’re dedicated to helping our more than 1,500 customers in over 50 countries, providing solutions and services to over 200,000 sites.

The Opportunity:

If you love to develop great quality software and are eager to learn new technologies and develop new skills, then we have a great opportunity for you: join our PDI family and work closely with other talented PDI engineers to deliver solutions that delight our customers every day!

As a Data Engineer III, you will be part of an agile data services team responsible for developing and maintaining our industry-leading cloud-based big data and data analytics infrastructure serving major global fortune 500 companies. The candidate will help with design, development, unit testing, performance testing, deployment, troubleshooting, defect resolution, and support of our

Job Responsibilities:

Utilize architectural and design skills for a variety of data-oriented tasks.
Establish and maintain strong relationships with business stakeholders.
Build highly reliable & scalable data systems with good data governance that provide complete, secure, accurate and timely data for analytics.
Expertise in data & dimensional modeling with good business acumen in supporting new product features and services - including financial reporting. 
Assist development and analytics organization to meet its delivery goals with regards to data design, flow and infrastructure.
Perform Data Modeling, Big data architecture design, support and implementation of OLTP, real time OLAP/data warehouse systems and ETL pipelines.
Track/Build & monitor data/system KPI’s like storage, performance & usage
Hands on administration of big data databases/compute engines (Redshift, EMR, Spark or similar) and optimization/tuning techniques
Prepare required documentation as outlined by departmental standards.
Identify, analyze and back track data problems as needed.
Provide recommendations for application and system improvements.
Mentor other team members
Work with business users to understand business requirements, issues and business and/or client processes.
Develop, test, and maintain high-performance of our data systems to meet the requirements of the business and/clients while adhering to departmental standards.
Perform quality assurance testing for all work performed.
Meet with agile teams as required to define and document application requirements.
Follow project development, deployment process & maintain industry standards and best coding practices.
Maintain security and organization of the company’s data.
Provide off-hour support as assigned.
Gather business requirements/features, estimate the tasks, design & develop scalable solutions.
Work with manager to ascertain the company’s data requirements.
Plan work to meet project deadlines, accommodate demands by development teams, set priorities and escalate issues appropriately.
 Provide recommendations to development teams for data restructuring and performing complex maintenance.
Deploy and manage changes in development, staging and production.
Assist development and dev ops teams on SQL queries and tuning.

Required Skills & Experience:

At least 7 years’ experience in data engineering, Data modeling, SQL, ETL, Big database, Data warehousing & basic-level administration of data infrastructure
At least 7 years coding experience in Java, Python, R or other equivalent programming language
At least 4 years big data experience
At least 2 years’ experience as technical lead architecting data lake/data warehouse/lake house systems & mentoring team of Data Engineers / DBAs
Proficient in a variety of big-data tools and technologies, including Hadoop, Spark, etc., handling different storage formats like Parquet, Delta/Apache Hudi/Apache Iceberg, & managing/working with different OLTP systems & data ingestion mechanisms.
Experience building large scale data lakes & warehouse systems leveraging cloud environments including AWS technologies –S3, Redshift, Aurora/RDS, DMS, EC2, Glue spark, Cloud watch, & EMR
Experience with data orchestration tools like Airflow
Experience in building pipelines, ingesting data from heterogeneous systems onto data lake environments in real time
Proficient in Python, SQL and PL-SQL, query tuning, optimization, ETL, ELT, and Data Warehousing
Proficient in Business Intelligence (BI), analytic database and products, able to take business requirements and translate into database tables, pipeline design and tasks.
General data-specific concepts, frameworks and processes
Agile development practices
Working within an SDLC
Designing data warehouses including definition, structure, documentation, maintenance, long-range requirements, operational guidelines, and protection
Data governance, meta data management, data security measures, retention & archival across data lake layers

Other Skills and Experience

Cloud experience, such as AWS, GCP or Azure
Building/Managing data lake & lake house architectures.
Experience working on different data lake storage formats.
Excellent oral and written communication
Multi-tasking and managing multiple priorities.
Working well in a team-oriented, collaborative environment with people from different disciplines and varying degrees of technical experience
Working in an Agile team environment.

Behavioral Competencies:

Cultivates Innovation

Decision Quality

Manages Complexity

Drives Results

Business Insight

PDI is committed to offering a well-rounded benefits program, designed to support and care for you, and your family throughout your life and career. This includes a competitive salary, market-competitive benefits, and a quarterly perks program. We encourage a good work-life balance with ample time off [time away] and, where appropriate, hybrid working arrangements. Employees have access to continuous learning, professional certifications, and leadership development opportunities. Our global culture fosters diversity, inclusion, and values authenticity, trust, curiosity, and diversity of thought, ensuring a supportive environment for all.

About the Company

PDI Technologies

Retail payment, loyalty, shopper insights

PDI Technologies provides payment solutions, loyalty programs, and shopper insights tailored for retail and convenience sectors, including petroleum wholesale. It offers software and related services that help businesses process payments, run loyalty initiatives, and analyze shopper data to improve engagement. The product suite works by integrating payment processing with loyalty and data analytics, enabling clients to manage customer programs, track transactions, and extract insights while ensuring data security. The company differentiates itself through deep industry specialization, more than four decades of experience, and a large, diverse client base (over 1,500 companies) in retail, convenience, and petroleum wholesale, which enables more precise, sector-specific solutions. Its goal is to help clients streamline operations, boost profitability, and grow customer loyalty by leveraging data-driven decisions and secure, integrated technology.

Company size: 1,001-5,000
Company stage: Not listed
Total funding: Not listed
Headquarters: Alpharetta, GA
Founded: 1983

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