Senior Data Engineer in United

Energy Jobline ZR; United (WV); On-site; USD 120,000 - 165,000; Full time

Job summary

Energy Jobline ZR is seeking a Senior Data Engineer to join a growing data team responsible for cloud-based data platforms powering analytics, AI, and decision-making. You will design and build scalable data pipelines, integrate sources, and enable analytics teams with trusted datasets.

You will work across a modern data stack, optimize performance, and contribute to data governance and platform reliability in a fast-paced environment.

Qualifications

• 5+ years of experience in data engineering or related field.
• Proficient in Python programming and SQL with experience in data frameworks and APIs.
• Hands-on Snowflake and cloud data platforms experience.
• Experience building production ELT/ETL pipelines.
• Familiar with Airflow and modern data stack.
• Knowledge of data modeling, warehousing concepts, and governance.

Responsibilities

• Design, develop, and maintain scalable data pipelines using Python, SQL, and cloud technologies.
• Ingest data from APIs, SaaS apps, databases, and external providers.
• Build ELT/ETL workflows into Snowflake data platform.
• Develop bronze and silver datasets within a medallion architecture framework.
• Implement data quality checks, monitoring, and observability processes.
• Troubleshoot production issues and data discrepancies.
• Collaborate with Analytics Engineers, Data Scientists, Product teams, and stakeholders.
• Contribute to data governance, metadata management, and platform best practices.
• Optimize pipeline performance, scalability, and operational efficiency.
• Drive DataOps, automation, and engineering standards improvements.

Skills

Python programming

SQL

Data modeling

Data warehousing

Data quality

Observability

ETL/ELT pipelines

Problem solving

Tools

Snowflake

Airflow

Databricks

Kafka

dbt

Informatica IDMC

Event Hubs

AWS

Azure

GCP

Job description

Job Description

About the Opportunity

We are seeking a hands‑on Senior Data Engineer to join a growing Data Engineering team focused on building modern, cloud-based data platforms that power analytics, reporting, AI, and business decision-making.

This is an opportunity to work on large-scale data challenges within a company undergoing significant investment in data modernization and AI initiatives. You'll help design and build data pipelines, integrate new data sources, improve data quality, and enable downstream analytics teams with trusted, scalable datasets.

The ideal candidate enjoys solving data movement problems, building production‑grade pipelines, and working across a modern data stack in a fast‑moving, highly collaborative environment.

What You'll Do

• Design, develop, and maintain scalable data pipelines using Python, SQL, and cloud- technologies.
• Ingest and integrate data from APIs, SaaS applications, enterprise systems, databases, and external data providers.
• Build and optimize ELT/ETL workflows that move data into a centralized Snowflake data platform.
• Develop and maintain bronze and silver layer datasets within a medallion architecture framework.
• Implement data quality checks, validation rules, monitoring, and observability processes.
• Troubleshoot production issues, investigate data discrepancies, and support platform reliability.
• Partner closely with Analytics Engineers, Data Scientists, Product teams, and business stakeholders to deliver trusted datasets.
• Contribute to data governance, metadata management, and platform best practices.
• Optimize pipeline performance, scalability, and operational efficiency.
• Drive continuous improvement in DataOps, automation, and engineering standards.

Required Qualifications

• 5+ years of experience in Data Engineering or a related field.
• Strong Python programming skills, including experience working with data frameworks and APIs.
• Advanced SQL skills with experience building complex transformations and analytical datasets.
• Hands‑on experience with Snowflake and modern cloud data platforms.
• Experience designing and maintaining ELT/ETL pipelines in production environments.
• Experience with orchestration tools such as Airflow.
• Experience working with cloud platforms such as Azure, AWS, or GCP.
• Strong understanding of data modeling, dimensional modeling, and data warehousing concepts.
• Experience implementing data quality, monitoring, and observability practices.
• Ability to support and troubleshoot production data pipelines.

Qualifications

• Experience with Databricks, Kafka, Event Hubs, or other streaming technologies.
• Experience with dbt and modern data transformation frameworks.
• Familiarity with CDC, incremental processing, and real‑time data architectures.
• Experience working within a medallion architecture (Bronze/Silver/Gold).
• Exposure to Informatica IDMC or similar enterprise data integration platforms.
• Experience supporting AI, machine learning, or advanced analytics initiatives.
• Knowledge of data governance, lineage, privacy, and compliance frameworks.
• Experience working with large-scale transactional or customer data environments.