Senior Data Engineer

Greetings from Synergy Resource Solutions, a leading Recruitment Consultancy.

Our Client is an ISO 27001:2013 AND ISO 9001 Certified company, and pioneer in web design and development company from India. Company has also been voted as the Top 10 mobile app development companies in India. Company is leading IT Consulting and web solution provider for custom software, website, games, custom web application, enterprise mobility, mobile apps and cloud-based application design & development.

Company is ranked one of the fastest growing web design and development company in India, with 3900+ successfully delivered projects across United States, UK, UAE, Canada and other countries. Over 95% of client retention rate demonstrates their level of services and client satisfaction.

Position : Senior Data Engineer

Experience : 5+ Years relevant experience

Education Qualification : Bachelor's or Master’s degree in Computer Science, Information Technology, or a related field.

Job Location : Ahmedabad

Shift : 11 AM – 8.30 PM

Key Responsibilities:

Our client seeking an experienced and motivated Senior Data Engineer to join their AI & Automation team. The ideal candidate will have 5–8 years of experience in data engineering, with a proven track record of designing and implementing scalable data solutions. A strong background in database technologies, data modeling, and data pipeline orchestration is essential. Additionally, hands-on experience with generative AI technologies and their applications in data workflows will set you apart. In this role, you will lead data engineering efforts to enhance automation, drive efficiency, and deliver data driven insights across the organization.

Job Description:

• Design, build, and maintain scalable, high-performance data pipelines and ETL/ELT processes across diverse database platforms.

• Architect and optimize data storage solutions to ensure reliability, security, and scalability.

• Leverage generative AI tools and models to enhance data engineering workflows, drive automation, and improve insight generation.

• Collaborate with cross-functional teams (Data Scientists, Analysts, and Engineers) to understand and deliver on data requirements.

• Develop and enforce data quality standards, governance policies, and monitoring systems to ensure data integrity.

• Create and maintain comprehensive documentation for data systems, workflows, and models.

• Implement data modeling best practices and optimize data retrieval processes for better performance.

• Stay up-to-date with emerging technologies and bring innovative solutions to the team.

Qualifications:

• Bachelor's or Master’s degree in Computer Science, Information Technology, or a related field.

• 5–8 years of experience in data engineering, designing and managing large-scale data systems.

Strong expertise in database technologies, including:

The mandatory skills are as follows:

1. SQL
2. NoSQL (MongoDB or Cassandra, or CosmosDB)
3. One of the following: Snowflake or Redshift or BigQuery or Microsft Fabrics
4. Azure

• Hands-on experience implementing and working with generative AI tools and models in production workflows.

• Proficiency in Python and SQL, with experience in data processing frameworks (e.g., Pandas, PySpark).

• Experience with ETL tools (e.g., Apache Airflow, MS Fabric, Informatica, Talend) and data pipeline orchestration platforms.

• Strong understanding of data architecture, data modeling, and data governance principles.

• Experience with cloud platforms (preferably Azure) and associated data services.

Skills:

• Advanced knowledge of Database Management Systems and ETL/ELT processes.

• Expertise in data modeling, data quality, and data governance.

• Proficiency in Python programming, version control systems (Git), and data pipeline orchestration tools.

• Familiarity with AI/ML technologies and their application in data engineering.

• Strong problem-solving and analytical skills, with the ability to troubleshoot complex data issues.

• Excellent communication skills, with the ability to explain technical concepts to non-technical stakeholders.

• Ability to work independently, lead projects, and mentor junior team members.

• Commitment to staying current with emerging technologies, trends, and best practices in the data engineering domain.