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
Skills Required
- At least 7 years of experience in data engineering, data modeling, SQL, ETL, big databases, data warehousing, and basic data infrastructure administration
- 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 technically leading and architecting data lake, data warehouse, or lakehouse systems and mentoring data engineers or DBAs
- Proficiency with Hadoop, Spark, Parquet, Delta, Apache Hudi, Apache Iceberg, OLTP systems, and data ingestion mechanisms
- Experience building large-scale data lakes and warehouse systems in AWS, including S3, Redshift, Aurora/RDS, DMS, EC2, Glue Spark, CloudWatch, and EMR
- Experience with data orchestration tools such as Airflow
- Experience building real-time data pipelines from heterogeneous systems into data lakes
- Proficiency in Python, SQL, PL/SQL, query tuning, optimization, ETL, ELT, and data warehousing
- Proficiency in business intelligence and analytical databases and translating business requirements into database tables, pipeline designs, and tasks
- Knowledge of data-specific concepts, frameworks, and processes
- Experience with Agile development practices and SDLC processes
- Experience designing, documenting, maintaining, and protecting data warehouses
- Experience with data governance, metadata management, data security, retention, and archival across data lake layers
- Cloud experience with AWS, GCP, or Azure
- Experience building or managing data lake and lakehouse architectures
- Experience with different data lake storage formats
- Excellent oral and written communication skills
- Ability to multitask and manage multiple priorities
- Ability to work collaboratively with multidisciplinary teams and colleagues with varying technical experience
- Experience working in an Agile team environment
PDI Technologies Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about PDI Technologies and has not been reviewed or approved by PDI Technologies.
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Leave & Time Off Breadth — Leave and time off are seen as reasonably generous, with flexibility and hybrid options contributing to a stable work-life setup. Feedback suggests certain teams value remote work programs and reliable scheduling.
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Healthcare Strength — Healthcare coverage is described as comprehensive, including medical, dental, and vision, with life and disability insurance. Some comments note the insurance package as somewhat better than average in certain cases.
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Flexible Benefits — Workplace flexibility, including remote or hybrid arrangements, is highlighted for eligible roles. Feedback suggests flexibility and schedule control are appreciated across some departments.
PDI Technologies Insights
What We Do
PDI Technologies resides at the intersection of productivity and sales growth, delivering powerful solutions that serve as the backbone of the convenience retail and petroleum wholesale ecosystem. By “Connecting Convenience” across the globe, we empower businesses to increase productivity, make more informed decisions, and engage faster with their customers. www.pditechnologies.com








