The DataOps Engineer will be responsible for building, automating, and optimizing scalable data pipelines and ensuring data quality, availability, and governance. This role requires a strong foundation in cloud ecosystems, particularly Azure and AWS, and experience in establishing CI/CD pipelines and real-time data processing systems. The ideal candidate will work closely with cross-functional teams to enhance data reliability and operational efficiency.

Experience:

6+ years of experience in data engineering, DataOps, or related roles. Proven experience with cloud ecosystems such as Azure (Azure Data Factory, Synapse, Databricks) and AWS (Glue, S3, Redshift, Lambda). Strong programming skills in Python and proficiency in SQL; experience with Scala or Java is a plus. Hands-on experience with CI/CD tools like Jenkins, Azure DevOps, or GitHub Actions. Familiarity with big data technologies like Apache Spark, Hadoop, and Kafka.

Required Skills:

Expertise in building and automating data pipelines in cloud environments. Proficiency in data governance, lineage, and quality management frameworks. Experience with real-time data streaming platforms like Kafka or Azure Event Hubs. Deep understanding of Infrastructure as Code (IaC) tools like Terraform or CloudFormation. Strong debugging and performance optimization skills.

Soft Skills:

Analytical mindset with excellent problem-solving capabilities. Strong communication skills to work effectively with cross-functional teams. Proactive, self-driven, and focused on continuous improvement. Ability to manage multiple tasks and meet deadlines in a fast-paced environment.

Education:

Bachelor’s or master’s degree in computer science, Data Science, Information Systems, or a related field.