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Data Engineer​/BI Developer-DA&A

Job in Indiana Borough, Indiana County, Pennsylvania, 15705, USA
Listing for: Mastek Limited
Full Time position
Listed on 2026-08-06
Job specializations:
  • IT/Tech
    Data Engineering, Cloud Computing: Infrastructure & Operations
Salary/Wage Range or Industry Benchmark: 100000 - 150000 USD Yearly USD 100000.00 150000.00 YEAR
Job Description & How to Apply Below

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Data Operations Engineer What You'll Do Operations Support
  • Monitor and triage production data pipelines, ingestion jobs, and transformation workflows (e.g. dbt, Snowflake tasks)
  • Manage and resolve data incidents and operational issues, working cross-functionally with platform, data, and analytics teams
  • Develop and maintain internal tools/scripts for observability, diagnostics, and automation of data workflows
  • Participate in on-call rotations to support platform uptime and SLAs
Data Platform Engineering Support
  • Help manage infrastructure-as-code configurations (e.g., Terraform for Snowflake, AWS, Airflow)
  • Support user onboarding, RBAC permissioning, and account provisioning across data platforms
  • Assist with schema and pipeline changes, versioning, and documentation
  • Assist with setting up monitoring on new pipelines in metaplane
Data & Analytics Engineering Support
  • Diagnosing model failures and upstream data issues
  • Collaborate with analytics teams to validate data freshness, quality, and lineage
  • Coordinate and perform backfills, schema adjustments, and reprocessing when needed
  • Manage operational aspects of source ingestion (e.g., REST APIs, batch jobs, database replication, kafka)

(confirm the writeup with Jason Prentice)

ML-Ops & Data Science Infrastructure
  • Collaborate with the data science team to operationalize and support ML pipelines, removing the burden of infrastructure ownership from the team
  • Monitor ML batch and streaming jobs (e.g., model scoring, feature engineering, data preprocessing)
  • Maintain and improve scheduling, resource management, and observability for ML workflows (e.g., using Airflow, Sage Maker, or Kubernetes-based tools)
  • Help manage model artifacts, metadata, and deployment environments to ensure reproducibility and traceability
  • Support the transition of ad hoc or experimental pipelines into production-grade services
What We're Looking For

Required Qualifications
  • At least 2–4 years of experience in data engineering, Dev Ops, or data operations roles
  • Solid understanding of modern data stack components (Snowflake, dbt, Airflow, Fivetran, cloud storage)
  • Proficiency with SQL and comfort debugging data transformations or analytic queries
  • Basic scripting/programming skills (e.g., Python, Bash) for automation and tooling
  • Familiarity with version control (Git) and CI/CD pipelines for data projects
  • Strong troubleshooting and communication skills — you enjoy helping others and resolving issues
  • Experience with infrastructure-as-code (Terraform, Cloud Formation)
  • Familiarity with observability tools such as datadog
  • Exposure to data governance tools and concepts (e.g., data catalogs, lineage, access control)
  • Understanding of ELT best practices and schema evolution in distributed data systems
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