Senior Data Engineer, Data Management & BI
New
J
JobgetherData engineering
Fully remote position within the United States.Full-TimeSenior
Salary115,000 - 145,000 USD per year
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Job Details
- Experience
- 5+ years of hands-on data engineering experience
- Required Skills
- AWSSQLJavaData engineeringSparkCI/CDScalaData modelingGitHub Actions
Requirements
- Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Analytics, or a related field, or equivalent practical experience.
- 5+ years of hands-on data engineering experience designing, building, testing, deploying, and supporting production data pipelines.
- Strong knowledge of 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 or EMR Serverless, Glue, Step Functions, SNS, or SQS, or comparable technologies.
- Strong programming experience with 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, or SingleStore.
- Experience designing and maintaining CI/CD pipelines, source control workflows, automated testing, and deployments using GitHub Actions or similar tools.
- Understanding of Agile delivery, DevOps practices, incident response, production support, monitoring, and performance tuning.
- Ability to troubleshoot complex data, application, and platform issues.
- Experience integrating files, APIs, event streams, relational systems, data lakes, and data warehouse platforms is desirable.
- Familiarity with orchestration tools such as Apache Airflow, AWS Glue, or Amazon MWAA is preferred.
- Experience with Infrastructure as Code, cloud security, IAM, secrets management, or BI and reporting platforms is a plus.
Responsibilities
- Design, build, test, deploy, and maintain scalable pipelines for structured and semi-structured data.
- Translate business and product requirements into technical designs, data models, integration patterns, and execution plans.
- Build and optimize batch, event-driven, and serverless data-processing solutions using cloud services and distributed processing frameworks.
- Contribute to architecture decisions for data lakes, data warehouses, orchestration, metadata, APIs, and application integrations.
- Implement data quality controls, monitoring, alerting, and operational runbooks for production pipelines.
- Design and maintain CI/CD pipelines, automated testing, deployment workflows, and infrastructure-as-code practices.
- Partner with analytics, BI, product, and business teams to deliver documented data products and reporting solutions.
- Participate in Agile delivery, code reviews, release planning, incident response, and retrospectives.
- Mentor engineers and maintain technical documentation, architecture diagrams, and data lineage information.
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