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Strong employer brand, mid-level generic Data Engineer role, metro locations, and broad skillset attract many qualified applicants.
Core data engineering skills are highly transferable across industries despite consultancy-specific client collaboration.
Mandatory 5+ years, PySpark and cloud (GCP/AWS) experience increases filtering rigor.
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Develop and operate modern data architecture and end-to-end data solutions to meet key business objectives.
Build and deploy large-scale, intricate data processing pipelines using big data tools and distributed storage/computing platforms.
Collaborate with data scientists for scalable model implementations and ensure data governance, security, privacy, and quality.
5+ years of experience in Data Engineering.
Proficiency with Pyspark and cloud platforms GCP and AWS.
Experience building and operating data pipelines and managing distributed storage systems in production.
Knowledge of data modeling, use of analytical tools like Power BI or equivalents, and strong coding skills with clean, test-driven development.
Experienced in handling complex data engineering challenges across scalable distributed systems and modern frameworks (e.g., data mesh).
Able to manage stakeholder communication and influence technical excellence within cross-functional teams.
Capable of coaching and mentoring peers, taking accountability for delivery, and adapting to ambiguity and risks in dynamic environments.