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Known multinational brand, Hyderabad metro, and mid-senior data role increase competition.
Core Spark and cloud data engineering skills are highly transferable across industries.
Mandatory Spark, cloud, and distributed-data expertise plus managerial ownership increases shortlisting strictness.
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Lead and manage a team of 5–10 software and data engineers to deliver timely, high-quality distributed data processing solutions, primarily on Apache Spark.
Provide technical leadership for large-scale Spark-based data platforms including architecture, design, optimization, and troubleshooting of batch and real-time pipelines.
Collaborate with cross-functional stakeholders, manage delivery roadmaps, and drive engineering governance, continuous improvement, and team development.
Strong hands-on experience with Apache Spark including Spark Core, Spark SQL, Structured Streaming, and performance tuning.
Proven experience leading engineering teams and managing delivery of complex distributed data processing systems.
Proficiency in programming languages such as Scala, Java, or Python.
Work Experience Required: Not explicitly mentioned in the JD. Hybrid work location requiring minimum two days per week onsite.
Experienced mid-level engineering manager with a strong technical background in Spark and cloud-native data platforms (AWS and/or GCP).
Proven ability to balance hands-on technical leadership and people management to drive delivery, architecture decisions, and team growth.
Skillful collaborator able to translate business needs into engineering plans and influence cross-functional teams in a complex data environment.