Lead Data Engineer

Accellor is an AI-first digital transformation partner built for the next generation of enterprise. We help global organizations turn cloud, data, and AI into real, measurable business outcomes at scale.

At Accellor, people come first. You’ll be trusted, empowered, and challenged to solve meaningful problems, collaborate with exceptional teams, and continuously grow your skills while building solutions that matter.

Trusted by Fortune 100 companies and global innovators, we work across industries delivering AI solutions, data platforms, and product engineering using modern, scalable technologies. If you want your work to create real impact and shape the future of enterprise, Accellor is where it happens.

As a Lead Data Engineer, you will play a crucial role in architecting and implementing robust data engineering solutions. Your expertise in managing and optimizing data flows, migrations, and transformations will be vital in supporting our projects. The ideal candidate will possess a mix of technical skills and strategic vision, ensuring that we leverage data to its fullest potential, thus achieving our business objectives.

Responsibilities:

• Design and build scalable, high-performance data pipelines and architecture.
• Lead and mentor a team of data engineers, fostering a culture of best practices in data management and engineering.
• Collaborate with cross-functional teams to grasp business needs and translate them into technical requirements.
• Ensure data quality, integrity, and security throughout the data lifecycle.
• Stay updated with emerging technologies and industry trends to innovate and enhance our data practices.
• Contribute to the continuous improvement of our data infrastructure and processes.

Requirements

• 7+ years of experience in data engineering or a related field.
• Proficiency in programming languages such as Python, Java, or Scala.
• Strong knowledge of SQL and experience with database technologies (e.g., PostgreSQL, MySQL).
• Hands-on experience with ETL tools and data integration techniques.
• Excellent understanding of data modeling concepts and best practices.
• Ability to work collaboratively and communicate effectively with team members and stakeholders.
• Experience with cloud platforms (AWS, Azure, GCP) is a plus.
• Strong analytical, problem-solving skills, and attention to detail.
• Experience with big data technologies like Hadoop or Spark is advantageous.
• Certification in relevant technologies (e.g., AWS, Azure) would be beneficial.