Data Engineer

Mastek; United States; On-site; USD 120,000 - 170,000; Full time

Job summary

Mastek Limited in the United States is seeking a seasoned Data Engineer with hands-on experience in building scalable data pipelines using DBT, Snowflake, and Python. The role demands 8-10 years of relevant experience and a solid understanding of modern data engineering practices to support analytics, reporting, and BI needs.

You will design, develop, and optimize data pipelines, collaborate with analysts and stakeholders, and ensure data quality through testing frameworks while advancing CI/CD

Qualifications

• 8-10 years of hands-on data engineering experience.
• Deep expertise in DBT, Snowflake and Python.
• Experience with SQL and dimensional modeling.
• Experience with data pipelines orchestration (Airflow).
• Experience in cloud environments (AWS/Azure/GCP).

Responsibilities

• Design, develop, and maintain scalable data pipelines with DBT, Snowflake, and Python.
• Build data transformation workflows and doc/testing via DBT.
• Develop data ingestion and processing pipelines in Python.
• Optimize Snowflake data models and queries for large datasets.
• Ensure data quality with testing and validation frameworks.
• Collaborate with data analysts and stakeholders to define data requirements.
• Implement best practices for data modeling, version control, and orchestration.
• Monitor, troubleshoot, and resolve pipeline issues and bottlenecks.
• Maintain documentation for data workflows and pipelines.
• Deliver robust pipelines to support analytics and BI.

Skills

DBT

Snowflake

Python

SQL

Data modeling

Airflow

CI/CD

Cloud environments

Data quality

Communication

Tools

Airflow

DBT

Snowflake

Job description

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Job Title

Data Engineer (DBT, Snowflake, Python)

Expected Work Experience

8-10 Years

Job Location

USA

Job Summary

We are looking for a skilled Data Engineer with strong hands-on experience in building scalable and efficient data pipelines. The ideal candidate will have deep expertise in DBT, Snowflake, and Python, and a solid understanding of modern data engineering practices. Candidate must have relevant experience of 8-10 Years. You will be responsible for designing, developing, and optimizing data pipelines and transformation workflows to support analytics, reporting, and business intelligence needs.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines using DBT, Snowflake, and Python.
• Build and manage data transformation workflows using DBT (models, macros, testing, and documentation).
• Develop efficient data ingestion and processing pipelines using Python.
• Optimize Snowflake data models, queries, and performance for large-scale datasets.
• Ensure data quality, reliability, and consistency through testing and validation frameworks.
• Collaborate with data analysts, business teams, and stakeholders to understand data requirements.
• Implement best practices for data modeling, version control, and pipeline orchestration.
• Monitor and troubleshoot data pipeline issues and performance bottlenecks.
• Maintain clear and structured documentation for data workflows and pipelines.
• Deliver robust and scalable data pipelines that support analytics and reporting needs.
• Develop and maintain DBT-based transformation frameworks to standardize data transformations.
• Produce optimized Snowflake data models and queries for high-performance analytics.
• Ensure delivery of high-quality, reliable datasets for analytics and reporting.

Other Capabilities

• Ability to work effectively as a contractor in a cross-functional environment with data analysts, engineers, and business stakeholders.
• Strong problem-solving and analytical mindset with attention to detail and data quality.
• Capability to work on enterprise-scale data platforms and support complex data ecosystems.
• Adaptability to evolving data engineering tools, frameworks, and best practices.
• Good communication skills to explain technical concepts to non-technical stakeholders.

Qualifications and Skills

• 8-10 years of hands-on experience in Data Engineering, with a focus on building scalable data pipelines.
• Strong expertise in DBT (Data Build Tool), including models, macros, testing, and documentation.
• Solid experience with Snowflake, including data warehousing, performance tuning, and optimization.
• Strong expertise in Python for data processing and pipeline development.
• Good understanding of SQL and data modeling concepts (star schema, dimensional modeling).
• Experience with data pipeline orchestration tools (such as Airflow or similar).
• Familiarity with data quality and testing frameworks to ensure reliable datasets.
• Strong problem-solving and analytical skills for diagnosing and resolving data issues.
• Experience working in cloud environments (AWS, Azure, or GCP).
• Familiarity with CI/CD practices for data pipelines and automated deployments.
• Exposure to real-time or streaming data pipelines is a plus.
• Experience in enterprise-scale data platforms and large-scale data environments.
• Background or familiarity with Data Automation & AI, Data Engineering, Data Analytics, and Databricks or similar modern data platforms is an advantage.