Full Stack Engineer

Project Role : Full Stack Engineer

Project Role Description : Responsible for developing and/or engineering the end-to-end features of a system, from user experience to backend code. Use development skills to deliver innovative solutions that help our clients improve the services they provide. Leverage new technologies that can be applied to solve challenging business problems with a cloud first and agile mindset.

Must have skills : PostgreSQL

Good to have skills : NA

Minimum 5 Year(s) Of Experience Is Required

Educational Qualification : 15 years full time education

Project Role: Data Engineer

Project Role Description: Build and maintain data pipelines, ensures data quality, and optimizes performance using tools like Python, SQL, Airflow, and cloud platforms.

Must have skills: T-SQL or SnowSQL + Airflow or DBT or ETL + Python + AWS (S3, EC2, Lambda)

Good to have skills: CI/CD tools like GitHub, Jenkins

Minimum 4 Year(s) Of Experience Is Required

Educational Qualification: 15 years full time education

Summary:

As a Data Engineer you will be responsible to designs, builds, and maintains scalable data pipelines and infrastructure to support analytics, reporting, and machine learning. This role involves developing ETL/ELT workflows, optimizing data models, driving performance improvement to handle large datasets and complex analytical queries, and ensuring data quality and security across cloud platforms like AWS. Data Engineers collaborate with business, BI, and development team members to align data solutions with organizational goals.

Roles & Responsibilities:

Design, develop, and maintain database objects and data pipelines using PostgreSQL and Python.

Collaborate with business stakeholders and cross-functional teams to understand business requirements and translate them into technical solutions.

Write efficient SQL and PL/pgSQL code, including functions, procedures, and complex queries.

Maintain clear and accurate technical documentation.

Participate in code reviews to ensure quality and adherence to best practices.

Stay updated on PostgreSQL features and best practices for analytics and transactional systems.

Must Have Tools & Languages:

Python, SQL (T-SQL, SnowSQL)

Airflow, DBT, ETL

Snowflake or Postgres

AWS (S3, EC2, Lambda)

Nice to Have :

Tableau, Power BI

CI/CD tools like GitHub, Jenkins

Good To Have:

Experience in data modeling for analytical reporting and large-scale datasets.

Optimize SQL and PL/pgSQL code for performance and maintainability.

Tune performance for large datasets and high-volume workloads.