Senior Data Engineer - Remote Data Management & BI

Carbon Data Solutions

United States

Remote

USD 115,000 - 145,000

Full time

6 days ago

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Benefits offered by this job

Fully remote

Benefits package

Job summary

NBCUniversal is seeking a Senior Data Engineer, Data Mgmt and BI to design and support scalable data solutions enabling trusted analytics and reporting across the organization. You will partner with product, analytics, engineering, and business stakeholders to translate needs into reliable technical solutions, while mentoring others and improving data delivery, governance, testing, and observability.

The role emphasizes cloud-native data pipelines, CI/CD, data quality, and production readiness

Qualifications

Bachelor's degree in CS, Engineering, IS, Data Analytics or equivalent practical experience.
5+ years of hands-on data engineering experience designing, building, testing, deploying, and supporting production data pipelines.
Strong experience with data modeling, data architecture, ETL/ELT patterns, metadata, data quality, and data warehouse or data lake methodologies.
Hands-on experience with cloud data engineering services such as AWS S3, Lambda, Athena, EMR/EMR Serverless, Glue, Step Functions, SNS, SQS or comparable technologies.
Strong programming experience in Scala, Java, SQL, or similar languages used for data processing, automation, and integration.
Experience with distributed processing and modern data platforms such as Spark, Databricks, Snowflake, Apache Iceberg, Hive, Redshift, Postgres, SingleStore, or comparable technologies.
Experience designing and maintaining CI/CD pipelines, source control workflows, automated testing, and deployment practices using GitHub Actions or similar tools.
Strong understanding of Agile delivery, DevOps practices, incident response, production support, monitoring, and performance tuning.
Strong analytical and problem-solving skills with the ability to troubleshoot complex data, application, and platform issues.
Excellent written and verbal communication skills, including the ability to explain technical concepts clearly to engineers, product owners, business stakeholders, and leadership.

Responsibilities

Design, build, test, deploy, and maintain scalable data pipelines ingesting, transforming, validating, and publishing data.
Translate business requirements into technical designs, data models, and execution plans.
Develop reusable, maintainable code with emphasis on performance, observability, and long-term support.
Build and optimize batch, event-driven, and serverless data processing patterns using cloud-native services.
Contribute to architecture decisions across data lake, warehouse, orchestration, metadata, API, and integration patterns.
Implement data quality checks, monitoring, and runbooks for production reliability.
Design and maintain CI/CD pipelines and infrastructure-as-code patterns.
Partner with analytics, BI, product, and business teams to enable trusted data products and reporting.
Evaluate source systems, APIs, files, data contracts, and transformation logic to identify risks and gaps.
Participate in Agile delivery practices including sprint planning, backlog refinement, code reviews, and retrospectives.
Mentor engineers and promote engineering best practices.
Create and maintain technical documentation, architecture diagrams, data lineage notes, and implementation guides.