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Moderate competition: mid-level analytics engineer in Hyderabad with Databricks/AWS skills at a known pharma.
Medium—strong Databricks/AWS data engineering skills are transferable, though pharma commercial dataset experience is advantageous.
High due to explicit 6+ years and mandatory Databricks, Delta Lake, and AWS production experience.
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Own design, build, and maintenance of scalable analytics-layer transformations and data models on Databricks for commercial analytics and reporting.
Lead technical decisions on Databricks and AWS architecture, including performance tuning, cost optimization, and data governance for large-scale datasets.
Mentor junior developers through hands-on coaching while collaborating with stakeholders to define metrics, data models, and governed datasets enabling self-service analytics.
6+ years of hands-on experience in analytics engineering or related roles, specifically with Databricks, data modeling, and AWS in production environments.
Strong proficiency in Databricks (notebooks, jobs/workflows, Unity Catalog) and Delta Lake (ACID tables, performance tuning, partitioning).
Expertise in dimensional data modeling (star/snowflake schemas, conformed dimensions, SCD handling) and AWS services (S3, IAM, Glue, Lambda).
Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, Statistics/Mathematics, or related field, or equivalent experience.
Experienced in building and optimizing large-scale data pipelines and semantic models specifically on Databricks Lakehouse architecture.
Skilled in mentoring and working alongside junior developers with a focus on hands-on pairing, code reviews, and delivery.
Comfortable in collaborating with business stakeholders to translate complex requirements into well-governed, analytics-ready data products and managing technical-business communications.