Sr. Software Engineer

4-6 Years

Job Title: Data Engineer (Snowflake and MS SQL Server)

Job Summary: We are seeking an experienced Data Engineer with 4 6 years of expertise in SQL Server, Snowflake, and data engineering practices. The ideal candidate will be responsible for building scalable data solutions, analyzing existing ETL processes, and ensuring seamless data integration across platforms. This role requires strong analytical skills, hands-on development experience, and the ability to collaborate with cross-functional teams to support data-driven decision-making.

Must-Have Skills & Experience:

4 6 years of professional experience in data engineering.

Strong proficiency in Microsoft SQL Server (T-SQL, stored procedures, indexing, performance optimization).

Proven hands-on experience with Snowflake (database creation, query optimization, data sharing, and schema management).

Solid understanding of ETL/ELT concepts and data warehousing principles.

Experience reviewing, analyzing, and troubleshooting SSIS packages (no development required).

Strong knowledge of data modeling, query performance tuning, and optimization techniques.

Excellent problem-solving skills and ability to work both independently and in a team environment.

Strong communication skills for collaborating with business and technical stakeholders.

Key Responsibilities:

Design, build, and optimize data pipelines and integration flows between SQL Server and Snowflake.

Review and analyze existing SSIS packages to identify improvements, troubleshoot issues, and recommend optimizations.

Develop, maintain, and tune complex SQL queries, stored procedures, and triggers.

Implement and manage data warehousing solutions in Snowflake to support reporting and analytics.

Collaborate with business analysts, data scientists, and application teams to gather requirements and deliver robust data solutions.

Conduct data validation, quality checks, and error handling to ensure accuracy and reliability of business reporting.

Ensure adherence to data governance, best practices, and documentation standards.

Participate in troubleshooting, root cause analysis, and performance enhancement activities.

Domain/ Industry Knowledge:

• Basic knowledge of customers business processes and relevant technology platform or product


• Able to prepare process maps, workflows, business cases and simple business models in line with customer requirements with assistance from SME and apply industry standards/ practices in implementation with guidance from experienced team members.

Requirement Gathering and Analysis:

• Basic knowledge of requirement management processes and requirement analysis process, tools and methodologies.


• Able to prototype/ design a prototype of an example system to be demonstrated to stakeholders and extract functional/ non-functional requirements from business requirements and document a system/ software requirements specification for low to medium complexity scenarios.

Product/ Technology Knowledge:

• Working knowledge of technology product/platform standards and specifications.


• Able to implement code or configure/customize products and provide inputs in design and architecture adhering to industry standards/ practices in implementation.


• Analyze various frameworks/tools, review the code and provide feedback on improvement opportunities.

Architecture tools and frameworks:

• Basic knowledge of architecture Industry tools & frameworks


• Able to analyse available tools and frameworks for review by the SME and plan (under guidance) for tool configurations and development.

Architecture concepts and principles:

• Basic knowledge of architectural elements, SDLC, methodologies.


• Able to apply various architectural constructs in the projects and identify various architectural patterns and implement.

Analytics Solution Design:

• High-level awareness of wide range of core data science/analytics techniques, its advantages, disadvantages, and areas of application.

Tools & Platform Knowledge:

• Familiar with wide range of mainstream commercial and open-source data science/analytics software tools, their constraints, advantages, disadvantages, and areas of application.

Accountability:

• Takes ownership for and ensures accuracy of own work, meets deadlines, and asks questions about possible gaps to ensure clarity of ownership.

Agility:

• Demonstrates a willingness to accept and embrace differing ideas or perceptions which are beneficial to the organization.

Collaboration:

• Participates in team activities and reaches out to others in team to achieve common goals.

Customer Focus:

• Displays awareness of customers stated needs and gives priority to meeting and exceeding customer expectations at or above expected quality within stipulated time.

Communication:

• Effectively communicates in written and oral form, well-organized thoughts to others. Speaks openly and honestly with all employees.

Drives Results:

• Demonstrates a "can do" attitude and is willing to stretch self to achieve and exceed defined goals/targets.