Zemoso is a unique services organization that specializes in early-stage initiatives and solves tough technology problems. We partner with startups, Fortune 500 companies, and mid-sized organizations on digital transformation, business model transformation, and new product development initiatives. We bring an expert understanding of how a focus on usability works with mature engineering practices to deliver the best outcomes for our customers. Every member of our team showcases accountability and ownership.
As a services organization, our people are our strongest asset. Therefore, we are committed to their career progression. Our Talent Nurture team organizes bootcamps, provides external resources, and hosts tailored workshops. We work on the most cutting-edge solutions, ensuring that our people stay up-to-date with the latest processes, technologies, and tools.
Location
Hyderabad/Pune/Bangalore/Chennai/Mumbai
Responsibilities
Python Proficiency:
Demonstrate a strong command of the Python programming language, actively contributing to the development and maintenance of data engineering solutions.
Data Engineering Expertise:
Set up and maintain efficient data pipelines, ensuring smooth data flow and integration across systems. Experience with SQL, and data warehouse/data lakes is required. Contribute to the establishment and maintenance of data lakes, implementing industry best practices. Execute data scrubbing techniques, and implement data validation processes to ensure data integrity and quality.
Tool and Platform Proficiency:
Experience with PySpark and/or the Databricks platform is required. Apart from this, expertise in at least one popular tool/platform within the data engineering domain will be nice to have. Stay informed about industry trends, exploring, and adopting tools to optimize data engineering processes.
Collaboration and Communication:
Collaborate effectively with cross-functional teams, including data scientists, software engineers, and business analysts. Communicate technical concepts to non-technical stakeholders, fostering collaboration and innovation within the team.
Documentation and Best Practices:
Contribute to maintaining comprehensive documentation for data engineering processes, ensuring knowledge transfer within the team. Adhere to best practices in data engineering, promoting a culture of quality and efficiency.
Required skills and qualifications
Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field
Minimum of 4 years of proven experience as a data engineer
Strong proficiency in Python programming language and SQL
Experience in setting up and managing data pipelines, data warehouses/lakes
Good comprehension and critical thinking skills
Good to have
Exposure to cloud-based data platforms (AWS, Azure, Google Cloud Platform (GCP)), and PySpark
Basic knowledge of big data technologies such as Hadoop, Spark, or Snowflake
Familiarity with containerization tools like Docker, or Kubernetes
Interest in data visualization tools (Tableau, PowerBI, etc.)
Certifications in relevant data engineering, or machine learning technologies
