PT
Senior Data Analyst
PYXIDIA TECHLAB
Mangaluru · On-site Full-time Senior Today
About the role
About the Role
We are looking for a Senior Data Analyst who will play a critical role in designing, building, and scaling data solutions across our products and client implementations. As a Senior Data Analyst, you will work closely with Product, Engineering, Data Science, and Client‑facing teams to translate complex business and healthcare use cases into robust, scalable data models and pipelines. You will be expected to mentor junior analysts, influence data design decisions, and ensure data quality, reliability, and performance at scale.
Role & Responsibilities
- Own the design, development, and operation of scalable data pipelines across structured and unstructured data sources.
- Build and optimize ETL/ELT workflows using SQL, Python, PySpark, and AWS big data technologies.
- Define and enforce data quality, validation, and monitoring standards to ensure accuracy and trust in data.
- Perform advanced data exploration and analysis to solve ambiguous business problems and deliver actionable insights.
- Act as a senior data owner during product and client implementations, ensuring data use cases are correctly implemented, tested, and production‑ready.
- Collaborate with Product, Engineering, and Data Science teams on data architecture and analytical use cases.
- Provide technical leadership and mentorship to junior analysts and contribute to data platform best practices.
Required Skills & Experience
- 4+ years of experience in Data Analytics / Data Engineering roles.
- Strong expertise in SQL and hands‑on experience with relational and NoSQL databases.
- Advanced experience with Python and PySpark for large‑scale data processing.
- Proven experience building & managing ETL pipelines using tools such as Airflow, AWS Glue, or similar.
- Strong understanding of data modeling and performance optimization.
- Experience working with AWS data services (S3, EMR, Redshift, Athena, RDS, etc.).
- Ability to own complex data problems end‑to‑end and influence cross‑functional stakeholders.
- Exposure to US healthcare data is a strong plus.
Requirements
- Strong expertise in SQL and hands-on experience with relational and NoSQL databases.
- Advanced experience with Python and PySpark for large-scale data processing.
- Proven experience building & managing ETL pipelines using tools such as Airflow, AWS Glue, or similar.
- Strong understanding of data modeling and performance optimization.
- Experience working with AWS data services (S3, EMR, Redshift, Athena, RDS, etc.).
- Ability to own complex data problems end-to-end and influence cross-functional stakeholders.
Responsibilities
- Own the design, development, and operation of scalable data pipelines across structured and unstructured data sources.
- Build and optimize ETL/ELT workflows using SQL, Python, PySpark, and AWS big data technologies.
- Define and enforce data quality, validation, and monitoring standards to ensure accuracy and trust in data.
- Perform advanced data exploration and analysis to solve ambiguous business problems and deliver actionable insights.
- Act as a senior data owner during product and client implementations, ensuring data use cases are correctly implemented, tested, and production-ready.
- Collaborate with Product, Engineering, and Data Science teams on data architecture and analytical use cases.
- Provide technical leadership and mentorship to junior analysts and contribute to data platform best practices.
Skills
AWS GlueAWS RDSAWS RedshiftAWS S3AthenaDockerEMRETLLambdaNoSQLPostgreSQLPythonPySparkSQL
Don't send a generic resume
Paste this job description into Mimi and get a resume tailored to exactly what the hiring team is looking for.
Get started free