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Strong brand, Bangalore metro, mid-level generalist role with broad skillset drives high applicant competitiveness.
Technical data engineering skills are broadly transferable, though domain knowledge in media/advertising moderately matters.
Explicit 5+ years and multiple mandatory cloud, Spark, Databricks, and language requirements enforce strict shortlisting.
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Design, develop, and maintain scalable data pipelines and data products using Scala, Python, Spark, and cloud technologies to support sports and preferences data for Disney Entertainment and ESPN.
Implement and evolve Lakehouse architecture collaborating with cross-functional teams to enhance data platform capabilities and ensure uptime SLAs.
Engage with stakeholders including Data Product Managers and Data Scientists to deliver high-quality data solutions and maintain documentation for governance and quality.
Minimum 5 years of experience in data engineering with developing large-scale data pipelines.
Strong programming skills in Scala and Python, with expertise in distributed systems like Spark and Hadoop.
Proficiency in cloud technologies, especially AWS (S3, EMR, EC2), and familiarity with MPP/cloud databases such as Snowflake, Redshift, or Big Query.
Bachelor’s degree in Computer Science, Information Systems, Software Engineering, Electrical/Electronics Engineering, or equivalent experience.
Experienced in building and managing data pipelines in large-scale, cloud-based environments with a focus on operational efficiency and meeting SLAs.
Comfortable working in agile/scrum teams and collaborating across data engineering, product management, and data science disciplines.
Capable of implementing modern data architectures (Lakehouse) and integrating diverse data technologies including Airflow and Databricks.