Senior Spark Data Engineer Careers at FirstEnergy: Remote Skills, Salary, Resume Tips & How to Get Hired
Senior Spark Data Engineers help companies build reliable data pipelines, process large datasets, support analytics teams, and create the data foundation behind smarter business decisions. In industries like energy, utilities, finance, healthcare, and technology, these roles are especially important because accurate data can directly affect customers, operations, reliability, and long-term planning.
The original FirstEnergy Senior Spark Data Engineer job previously featured on WorkinVirtual may no longer be open. This rebuilt guide will help you prepare for similar remote and hybrid Spark Data Engineer roles at FirstEnergy and other employers hiring cloud, big data, and analytics engineering talent.
Opportunity Snapshot
About FirstEnergy Careers
FirstEnergy is an electric utility company serving customers across multiple states. Technology and data teams in utility companies often support grid reliability, customer analytics, smart meter data, asset management, outage prediction, reporting, and digital transformation projects.
For current openings, always check the official FirstEnergy careers page before applying through any older job article.
Official FirstEnergy Careers Page: FirstEnergy Careers
What a Senior Spark Data Engineer Does
A Senior Spark Data Engineer designs, builds, optimizes, and maintains data pipelines that move information from raw systems into analytics, reporting, data science, and machine learning environments. This role often works with high-volume data, distributed processing systems, cloud platforms, and business teams that depend on accurate insights.
In an energy or utility environment, Spark Data Engineers may support customer usage analytics, smart meter insights, outage prediction, asset reliability, grid modernization, reporting platforms, and operational dashboards.
Common Responsibilities
- Design, build, and optimize scalable ETL and ELT data pipelines.
- Use Apache Spark to process large volumes of structured and semi-structured data.
- Work with cloud-based data platforms, data lakes, and lakehouse environments.
- Support analytics, reporting, data science, and machine learning teams.
- Create reliable data products for business users and technical teams.
- Improve data quality, performance, monitoring, and pipeline reliability.
- Collaborate with business analysts, solution architects, engineers, and product teams.
- Evaluate new data engineering tools and platform improvements.
- Mentor junior data engineers and support engineering best practices.
- Document data architecture, pipelines, dependencies, and production processes.
Skills Employers Want
- Apache Spark
- Python
- SQL
- ETL and ELT pipeline development
- Databricks
- Data lake and lakehouse architecture
- Cloud platforms such as AWS, Azure, or Google Cloud
- Data modeling
- Big data processing
- Airflow, Kafka, or similar workflow tools
- DevOps and CI/CD practices
- Git and version control
- Data quality testing
- Performance tuning
- Stakeholder communication
Salary Context
Senior Spark Data Engineer compensation can vary based on experience, location, cloud expertise, industry, team leadership, and whether the role is remote, hybrid, or tied to a specific office.
- Data Engineer: $95,000–$130,000
- Senior Data Engineer: $125,000–$165,000
- Senior Spark Data Engineer: $135,000–$180,000+
- Lead Data Engineer / Data Platform Engineer: $160,000–$210,000+
Higher-paying roles usually require strong Spark performance tuning, cloud data platform experience, production pipeline ownership, data modeling, and the ability to mentor other engineers.
Resume Tips for Senior Spark Data Engineer Jobs
- Lead with Spark, Python, SQL, cloud platforms, and data pipeline achievements.
- Show the scale of data you worked with, such as volume, frequency, processing time, or number of users served.
- Include measurable wins such as faster pipeline performance, reduced cloud cost, improved data quality, or better reporting reliability.
- Mention specific platforms such as Databricks, Snowflake, BigQuery, Redshift, Azure Data Factory, Airflow, Kafka, or Delta Lake.
- Show experience supporting analytics, machine learning, and business intelligence teams.
- Highlight mentoring, architecture input, code reviews, and production ownership.
- Avoid generic bullets like “worked with data.” Explain what you built, improved, automated, or scaled.
Interview Preparation
For Senior Spark Data Engineer interviews, expect questions about distributed processing, pipeline design, data quality, performance tuning, cloud architecture, and production troubleshooting.
- How would you design a scalable data pipeline for smart meter or customer usage data?
- How do you optimize slow Spark jobs?
- What causes data skew in Spark, and how do you handle it?
- How do you choose between batch and streaming pipelines?
- How do you monitor and recover failed ETL jobs?
- How do you ensure data quality before analytics teams use a dataset?
- Describe a pipeline you improved for performance or cost.
- How do you work with business analysts and data scientists?
- What is your experience with Databricks, Delta Lake, or cloud data platforms?
- How do you document production data pipelines?
Similar Job Titles to Search
- Senior Spark Data Engineer
- Senior Data Engineer
- Big Data Engineer
- Cloud Data Engineer
- Data Platform Engineer
- ETL Developer
- Databricks Engineer
- Analytics Engineer
- Data Lake Engineer
- Lead Data Engineer
Find Remote Data Engineering Jobs
Ready to apply for similar roles? Browse current remote jobs, explore companies hiring remote workers, search the WorkinVirtual jobs board, or upload your resume so employers can discover your profile.
Helpful Career Tool: Use the WorkinVirtual Resume Improvement Advisor to strengthen your Spark, cloud, SQL, and data pipeline resume before applying.
Browse Remote JobsEditorial Note: This article was rebuilt from an older job post that may no longer be active. It has been updated into an evergreen career guide to help remote job seekers prepare for similar Senior Spark Data Engineer, Big Data Engineer, Cloud Data Engineer, and Data Platform Engineer opportunities.