Data Engineer

Paradigm Technology; South Carolina; On-site; USD 90,000 - 130,000; Full time

Job summary

Paradigm seeks a Data Engineer for a 6-month contract-to-hire opportunity in South Carolina. You will architect and deliver cloud-native data platforms and pipelines, mentor junior staff, and collaborate with executives to translate business requirements into scalable data products powering analytics and ML workflows.

Responsibilities include leading migrations to cloud warehouses, enforcing design standards, and ensuring data governance, privacy, and reliability while driving performance

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related discipline.
• 2-3+ years of Data Engineering experience (ETL/ELT, cloud warehousing, analytics).
• Strong background in cloud data architecture, governance, performance optimization, and leadership communication.

Responsibilities

• Architect and develop enterprise-scale cloud data pipelines and warehousing solutions.
• Lead migration initiatives from legacy platforms to cloud-native data warehouses.
• Define and enforce ETL/ELT design standards, coding practices, and security controls.
• Build modular, reusable data components for analytics, reporting, and ML feature pipelines.
• Optimizes pipeline performance and establishes SLAs/monitoring.
• Provide technical leadership and mentor junior engineers; document frameworks.

Skills

Python

SQL

Databricks

Informatica

Cloud platforms

Education

Bachelor’s degree in CS/Engineering or related

Master’s degree preferred

Tools

Databricks

Informatica

Azure/AWS/GCP

Job description

• Seeking a Data Engineer for a 6-month contract-to-hire opportunity with a Utility client in South Carolina; must be able to drive to the office a few times a month
• Lead complex, enterprise-scale data engineering initiatives, architect cloud-native warehousing solutions, and mentor junior staff
• Design end-to-end ETL/ELT and analytics platforms using Databricks, Informatica, Python, SQL, and cloud services; set and enforce engineering standards; and engage stakeholders to translate business requirements into robust, secure, and performant data products that power analytics, reporting, and ML workflows
• Responsible for architecting and delivering cloud-native data platforms and pipelines that provide reliable, governed, and scalable data to the enterprise
• Operate with broad autonomy, collaborating with executive and technical stakeholders to translate requirements into engineering specifications, cost-aware architectures, and operational runbooks
• Ensure data governance (lineage, catalog, privacy), compliance, and resilience, while driving continuous improvement across performance tuning, incident response, and reliability engineering

Responsibilities:

• Architect and develop enterprise-scale cloud data pipelines and warehousing solutions
• Lead migration initiatives from legacy platforms to cloud-native data warehouses
• Define and enforce ETL/ELT design standards, coding practices, and security controls
• Build modular, reusable data components for analytics, reporting, and ML feature pipelines
• Optimizes pipeline performance (throughput, latency, reliability) and establish SLAs/monitoring
• Provide technical leadership and mentor junior engineers as well as document frameworks and patterns
• Engage stakeholders; translate business requirements into engineering specs and roadmaps
• Govern data quality, lineage, and cataloging; ensure compliance with privacy/security policies

Qualifications:

• Bachelor’s Degree in Computer Science, Engineering, or related discipline; Master’s Degree is preferred
• 2-3+ years of experience in Data Engineering (ETL/ELT, cloud warehousing, analytics) with advanced expertise in Databricks, Informatica, Python, SQL, and cloud data platforms
• Must have strong background in cloud data architecture, governance, performance optimization, and technical leadership communication

Required Experience:

• Languages and Platforms: Proficient in Python and SQL, Databricks (notebooks/jobs) and Informatica (ETL/ELT)
• Cloud Platforms: Hands-on experience with Azure/AWS/GCP, familiarity with storage, compute, IAM, and networking basics
• Data Warehousing: Modeling (dimensional/star), partitioning, Delta/Parquet, medallion architecture, and performance tuning
• Orchestration and Reliability: Job scheduling, retries, alerting, and CI/CD basics for data pipelines
• Data Governance and Quality: Validations, profiling, data contracts, lineage/catalog documentation, and adherence to privacy/security policies
• Collaboration and Delivery: Translate stakeholder requirements, produce clear documentation and reproducible code artifacts, and manage SLAs

Preferred Experience:

• Orchestration: Airflow/Prefect, event-driven and batch scheduling; SCD patterns and CDC/streaming (Kafka/EventHub)
• Platform Components: Delta Live Tables, Feature Stores, Databricks SQL/Unity governance, and Terraform/Bicep for infra-as-code
• Integration: APIs, semi-structured/unstructured data (JSON/Avro), file ingestion at scale, and federated/virtualized query layers
• Domain: Utility/energy datasets (AMI, SCADA) and compliance/governance in regulated environments

Why Join Paradigm

At Paradigm, integrity drives innovation. You’ll collaborate with curious, dedicated teammates, solving complex problems and unlocking immense data value for leading organizations. If you seek a place where your voice is heard, growth is supported, and your work creates lasting business value, you belong at Paradigm.

Learn more at https://pt-corp.com/

Policy Disclosure:

Paradigm maintains a strict drug-free workplace policy. All offers of employment are contingent upon successfully passing a standard 5-panel drug screen. Please note that a positive test result for any prohibited substance, including marijuana, will result in disqualification from employment, regardless of state laws permitting its use. This policy applies consistently across all positions and locations.

Data and AI Consulting for Digital Transformation

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