Data Engineer (Domain Change)

About the Role

We are looking for motivated professionals with 2+ years of experience who are passionate about transitioning their careers into Data Engineering. This opportunity is ideal for candidates from any technical domain who possess strong problem-solving skills, cloud knowledge, and a genuine interest in building scalable data solutions.

Candidates looking for a domain change into Data Engineering are highly preferred.

Key Responsibilities

• Learn and work on modern Data Engineering technologies and best practices.
• Design, develop, and maintain scalable data pipelines.
• Build ETL/ELT workflows for structured and unstructured data.
• Integrate data from multiple sources into cloud-based data platforms
• Ensure data quality, integrity, and reliability across data pipelines.
• Collaborate with cross-functional teams including Data Scientists, Analysts, and Software Engineers.
• Optimize data processing workflows for performance and scalability.
• Participate in code reviews, testing, deployment, and production support.

Required Skills

• 2+ years of professional experience in any technical domain.
• Knowledge of at least one cloud platform:
• AWS
• Microsoft Azure Google
• Cloud Platform (GCP)
• Strong programming knowledge in Python, Java, or Scala is preferred.
• Good understanding of SQL and relational databases.
• Basic understanding of ETL concepts and data warehousing.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration abilities.
• Willingness to build a long-term career in Data Engineering.

Qualification

• B.E. / B.Tech (Mandatory)
• Minimum 75% throughout academics (10th, 12th, and Graduation)
• Certification in Data Engineering or a related field is mandatory/preferred (e.g., AWS, Microsoft Azure, Google Cloud, Databricks, or equivalent Data Engineering certifications).

Preferred Candidate Profile

• Candidates seeking a career transition into Data Engineering.
• Certification in Data Engineering or an equivalent cloud/data platform certification.
• Exposure to cloud services on AWS, Azure, or GCP.
• Eagerness to learn Big Data technologies, ETL tools, Spark, Databricks, and modern data platforms.
• Ability to quickly adapt to new technologies and business domains.
• Passion for working with large-scale data systems.

Work Location: In person