Job Overview
Role: Software Engineer – Analytical Engineering Location: Hyderabad Experience: 1-3 Years Qualification: Academic background in Computer Science, Physics, Mathematics, Data Science, Pharmaceutical Science, or Engineering Key Skills: SQL, Spark, Python, Data Modeling, Analytical Engineering, ELT, dbt, AWS, Airflow, BI Tools
Job Description
Bristol Myers Squibb (BMS) is hiring a Software Engineer – Analytical Engineering in Hyderabad. This role is for candidates with 1–3 years of experience in analytical engineering, data modeling, or data engineering. The position bridges data engineering and data analytics, focusing on transforming raw data into structured, business-ready datasets to support business intelligence and data-driven decision-making. The engineer will develop analytical workflows, centralized data layers, scalable data products, and reliable pipelines, with proficiency in SQL, Spark, and Python being essential.
Roles and Responsibilities
- Data Transformation & Modeling: Develop and maintain core data models and the organization's core data layer; Transform raw data into structured, business-ready analytical datasets using an ELT framework (e.g., dbt).
- Pipeline Development: Develop analytical workflows, scalable data products, and reliable pipelines.
- Data Governance: Ensure data is reliable, structured, documented, and ready for use by analysts, BI teams, and AI/ML applications; Improve data consistency, reuse, governance, maintainability, and analytics efficiency.
- Collaboration: Work between traditional data engineering and analytics teams; Collaborate with AI and ML teams to develop data foundations for AI-enabled internal tools.
- Quality & Testing: Ensure data quality and implement testing strategies.
- Methodology: Work in an Agile environment and maintain DRY (Don't Repeat Yourself) code.
- Communication: Gather requirements, understand business needs, and communicate effectively with stakeholders.
Skills and Eligibility Criteria
Educational Background: Computer Science, Physics, Mathematics, Data Science, Pharmaceutical Science, Engineering.
Experience: 1–3 years of experience in analytical engineering, data modeling, or a similar role. Hands-on exposure to dbt is useful but not mandatory.
Mandatory Technical Skills:
- Proficiency in SQL (JOINs, CTEs, Subqueries, Window functions, Aggregations, CASE expressions, Date functions, Query optimization)
- Proficiency in Spark (DataFrames, Transformations and actions, Partitioning, Distributed processing, PySpark, Performance considerations)
- Proficiency in Python (Functions/modules, OOP, exception handling, file processing, data structures, APIs, NumPy, Pandas, Testing)
- Knowledge of data engineering tools such as AWS and Airflow
- Knowledge of visualization tools such as Tableau, Power BI, or Looker
- Experience with Git or SVN
- Foundational capability in data modeling (Entities, relationships, Fact/dimension tables, Star/Snowflake schemas, Primary/foreign keys, Granularity, Data quality)
Competencies:
- Analytical and problem-solving ability
- Developing ability to gather requirements and understand business needs
- Good communication and presentation skills
- Familiarity with AI, ML, and predictive modeling
- Agile development experience
- Teamwork and collaboration