🕒 yesterday
As a Senior Data Engineer, you will design and implement scalable data pipelines, ensuring data governance and supporting Headway's mission to improve access to mental healthcare.
Data Specialist - R01569581
📅 Aug 12
SnowflakeDbtSQLPython
📜 Description
- Build and maintain ETL/ELT pipelines using dbt, SQL, and Python.
- Develop and optimize Snowflake data warehouse solutions for analytics and reporting.
- Create data models and transformation frameworks; implement ingestion, cleansing, transformation, and validation.
- Maintain stored procedures, views, and database objects across cloud data platforms.
- Tune queries, models, and pipelines; monitor data quality and troubleshoot issues.
- Collaborate with stakeholders and engineering teams, and contribute to reviews, testing, deployment, documentation, governance, and security.
🛠️ Requirements
- 5–8 years of experience in data engineering.
- Strong hands-on Snowflake experience, including Snowpipe, Zero Copy Cloning, Time Travel, Fail Safe, SnowSQL, and data sharing.
- Strong dbt expertise, including reusable models, testing, documentation, and deployment.
- Advanced SQL skills, including query optimization, analytical functions, stored procedures, and large-scale datasets.
- Strong Python programming skills for data processing and automation.
- Knowledge of ETL/ELT, modern data architectures, data warehousing, dimensional modeling, governance, data quality, and metadata management.
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
- Preferred: Airflow, AWS/Azure/GCP, CI/CD, Git, BI tools, AI/GenAI, or relevant platform certifications.
Full job description
Lead Data Engineer
Primary Skills
Specialization
Job requirements
Job Title: Data Engineer – Snowflake, DBT, Python & SQL
Experience
5–8 Years
Location
Bangalore / Hyderabad / Pune / Chennai / Gurgaon
Job Summary
We are seeking a skilled Data Engineer with strong expertise in Snowflake, DBT, SQL, and Python to design, develop, and maintain scalable data solutions. The ideal candidate will have hands-on experience building modern data pipelines, implementing data warehouse solutions, and enabling analytics through efficient data modeling and transformation practices.
Key Responsibilities
- Design, build, and maintain scalable ETL/ELT data pipelines using DBT, SQL, and Python.
- Develop and optimize Snowflake-based data warehouse solutions for enterprise analytics and reporting.
- Create robust data models and transformation frameworks to support business requirements.
- Implement data ingestion, cleansing, transformation, and validation processes.
- Develop and maintain stored procedures, views, and database objects within cloud data platforms.
- Optimize SQL queries, data models, and pipelines for performance and scalability.
- Work closely with business stakeholders, analysts, and engineering teams to translate requirements into technical solutions.
- Monitor data quality and troubleshoot data-related issues across platforms.
- Leverage Snowflake features such as Snowpipe, Time Travel, Zero Copy Cloning, and Fail Safe.
- Participate in code reviews, testing, deployment, and documentation activities.
- Support data governance, security, and best practices across the data ecosystem.
- Strong hands-on experience with Snowflake Data Warehouse.
- Experience with:
- Snowpipe
- Zero Copy Cloning
- Time Travel
- Fail Safe
- SnowSQL
- Data Sharing/Data Exchange
- Performance tuning and optimization of Snowflake workloads.
- Strong expertise in DBT (Data Build Tool).
- Experience developing reusable transformation models.
- Understanding of DBT testing, documentation, and deployment practices.
- Advanced SQL skills with experience handling large-scale datasets.
- Expertise in query optimization, joins, analytical functions, and performance tuning.
- Experience with stored procedures and database development.
- Strong Python programming skills for data processing and automation.
- Experience with data engineering frameworks and scripting.
- Strong understanding of ETL/ELT concepts and modern data architectures.
- Experience in data warehousing and dimensional modeling.
- Knowledge of data governance, data quality, and metadata management.
- Experience with orchestration tools such as Airflow.
- Exposure to cloud platforms such as AWS, Azure, or GCP.
- Knowledge of CI/CD practices and Git-based version control.
- Experience with reporting and visualization tools such as Power BI, Tableau, or Looker.
- Exposure to AI/GenAI capabilities within data engineering solutions.
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
- Snowflake SnowPro Certification
- DBT Certification
- AWS/Azure/GCP Data Engineering Certifications
- Databricks or Cloud Data Platform Certifications
Required Skills
Snowflake
DBT
SQL
Python
Data Engineering
Preferred Skills
Educational Qualifications
Preferred Certifications
Primary Skills
Snowflake, DBT, SQL, Python
Secondary Skills
Data Modeling, ETL/ELT, Airflow, AWS/Azure/GCP, Power BI/Tableau, Data Warehousing
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