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Mid-level data engineer in Bangalore with broad, generalist requirements yields high competition.
Core data engineering skills are transferable, though Databricks and media dataset experience add specificity.
Requires 5+ years, strong Spark/cloud/warehousing expertise and a Master's, indicating high strictness.
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Design, build, and maintain large-scale, scalable data pipelines and cloud-based data infrastructure including messaging, storage, and orchestration components.
Collaborate with AI researchers, data scientists, and product teams to deliver data solutions and insights that shape product and user experience improvements.
Lead technical mentorship for junior data engineers and implement monitoring, alerting, and governance practices to ensure data quality and platform reliability.
5+ years of professional experience in data engineering focused on large-scale data pipelines and infrastructure.
Expert proficiency in at least one programming language: Python, Scala, or Java.
Hands-on experience with distributed data processing frameworks like Apache Spark and cloud platforms (AWS, GCP, or Azure).
Master’s degree in Computer Science, Data Science, or a related quantitative field.
Experienced in implementing and optimizing cloud-based data architectures using services like Databricks, Snowflake, Redshift, BigQuery, and data lakes (S3, HDFS).
Skilled in data modeling, schema design, SQL optimization, and orchestration/DevOps practices including Docker and Kubernetes.
Capable of providing technical leadership and mentorship within cross-functional teams, driving best practices in data engineering and governance.