Associate Data Scientist (Data Engineering)
Amgen View all jobs
- Hyderabad, Telangana
- Permanent
- Full-time
- Support building and maintaining data ingestion and transformation workflows (ETL/ELT) for marketing and media datasets
- Assist with implementing data validations and QA checks (schema checks, null checks, duplication checks, count reconciliation) to ensure datasets are reliable and analytics‑ready
- Help monitor pipeline runs and refresh schedules, investigate failures using logs, and escalate issues with clear context and evidence
- Support development of reusable, governed datasets / data products that are consistent and easy for BI and analytics teams to consume
- Contribute to documentation (data flow notes, runbooks, assumptions, source mapping) to improve operational stability and handoffs
- Collaborate with cross‑functional partners (MSO BI, MSO Ops, Analytics teams, Vendors) to ensure inputs and outputs are aligned and dependable
- Participate in continuous learning and improvement to strengthen engineering fundamentals, reliability practices, and delivery discipline
- Analyze and understand the functional & non-functional requirements for Investment and Media Analytics function, and translate them into prototype, technical specifications.
- Bachelor’s (3 to 6 Yrs) or Master’s (2 to 4 Yrs) degree in Computer Science, Engineering, Information Systems, Data Science, or a related quantitative/technical field
- Experience in data engineering, software engineering, analytics engineering, or data/tech role
- Familiarity with data concepts (tables, schemas, joins, basic transformations)
- Proficiency in SQL and data analysis and structured data
- Strong problem‑solving and analytical reasoning skills
- Effective written and verbal communication skills
- Strong learning mindset and willingness to work with new tools, datasets, and business contexts
- Exposure to Python programming for automation
- Exposure to cloud/data tools such as Databricks, Spark/PySpark, Azure/AWS, ADF/Airflow
- Experience with ETL/ELT pipelines, batch processing, or orchestration concepts
- Familiarity with data quality checks, profiling, data governance, logging, monitoring, or incident triage practices
- Exposure to DevSecOps practice