As a Senior Data Engineer, you will focus on designing scalable pipelines, mentoring junior engineers, and championing best practices in data engineering and MLOps.
Your contributions will ensure the reliability, scalability, and performance of our data and ML infrastructure, driving actionable insights and measurable impact for the business.
This role offers an excellent opportunity to deepen your expertise in modern data engineering and MLOps practices while working with cutting-edge technologies in a fast-evolving industry.
What We Expect from you :
Experience :
– Bringing 2+ years of expertise in data engineering, with a proven track record of designing and optimizing scalable solutions.
– Strong experience with cloud data warehouses and query engines
– Experience with data cataloging, metadata management, and lineage tools
– Experience with data quality tooling will be a plus.
Technical Expertise :
– Strong expertise in big data technologies such as SQL, PySpark and Hive
– Experience with big data workflow orchestrators like Argo Workflows
– Hands-on experience with cloud-based data stores like Redshift or BigQuery (preferred).
– Familiarity with cloud platforms, preferably GCP or Azure.
Development Practices :
– Strong programming skills in Python, with experience in frameworks like FastAPI or similar API frameworks.
– Proficiency in unit testing and ensuring code quality.
– Hands-on experience with version control tools like Git.
Optimization & Problem Solving :
– Ability to analyze complex data pipelines, identify performance bottlenecks, and suggest optimization strategies.
– Work collaboratively with infrastructure teams to ensure a robust and scalable platform for data science workflows.
Collaboration & Communication :
– Excellent problem-solving skills and the ability to work effectively in a team environment.
– Proven mentoring and communication skills, fostering collaboration across teams and effectively sharing technical expertise.
Nice To Have :
– Experience with microservices architecture, containerization using Docker, and orchestration tools like Kubernetes.
– Working knowledge of machine learning workflows with feature engineering, model training, deployment, and monitoring etc.
– Understanding of logging, monitoring, and alerting for production-grade big data pipelines.
– Good working knowledge with NoSQL databases such as MongoDB, Cassandra, or DynamoDB.
Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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