Data Ops Engineer-Remote Python,Snowflake,ETL, DBT, AWSTerraform

Mastek; India; Remote; INR 600,000 - 1,200,000; Full time

Job summary

Mastek is seeking a Data Operations Engineer to monitor and triage production data pipelines and ingestion workflows. You will resolve data incidents and collaborate with platform, data, and analytics teams to maintain uptime and SLAs.

You will also develop internal tools for observability, supporting infrastructure as code and data governance across Snowflake, Airflow, and cloud platforms. The role requires 2–4 years of related experience and strong scripting and SQL skills.

Qualifications

• 2–4 years of experience in data engineering, DevOps, or data operations roles.
• Solid understanding of modern data stack components (Snowflake, dbt, Airflow, Fivetran, cloud storage).
• Proficiency with SQL and debugging data transformations or analytic queries.
• Basic scripting/programming (e.g., Python, Bash) for automation and tooling.
• Familiarity with Git and CI/CD pipelines for data projects.
• Strong troubleshooting and communication skills for cross-functional support.
• Experience with infrastructure-as-code (Terraform, CloudFormation).
• Familiarity with observability tools such as Datadog.
• Exposure to data governance tools and concepts (data catalogs, lineage, access control).
• Understanding of ELT best practices and schema evolution in distributed data systems.

Responsibilities

• Monitor and triage production data pipelines, ingestion jobs, and transformation workflows (e.g., dbt, Snowflake tasks).
• Manage and resolve data incidents and operational issues 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.
• Help manage infrastructure-as-code configurations (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.
• 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).

Skills

SQL

Data engineering

DevOps

Python

Bash

Git

CI/CD

Terraform

Snowflake

dbt

Airflow

Fivetran

Datadog

Data governance

ELT

Tools

Snowflake

dbt

Airflow

Fivetran

Terraform

CloudFormation

Datadog

Job description

Role: Data Operations Engineer

What Youll 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)

What We’re Looking For

Required Qualifications

• At least 2–4 years of experience in data engineering, DevOps, 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, CloudFormation)
• 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