Data Engineer - Python/SQL

Key Responsibilities : Data Engineering & Analytics : - Design and develop cloud-native data pipelines (ETL/ELT) to collect, process, and transform large volumes of structured and unstructured data. - Build and optimize data models and data marts to support BI and self-service analytics. - Implement data ingestion frameworks from diverse sources (APIs, databases, flat files, real-time streams). Cloud Platform Expertise : Utilize services from cloud platforms like : - AWS (Glue, Redshift, Athena, S3, Lambda) - Azure (Data Factory, Synapse, Databricks, Blob Storage) - Google Cloud (BigQuery, Dataflow, Pub/Sub, GCS) - Manage and monitor data storage, transformation, and security across cloud environments. Data Visualization & Reporting : - Develop dashboards, reports, and visualizations using tools like: - Power BI, Tableau, Looker, Google Data Studio, or Qlik - Collaborate with business stakeholders to gather requirements and build analytics solutions. Governance, Security & Performance : - Ensure data quality, security, and compliance with policies (GDPR, HIPAA, etc.) - Implement data cataloging, lineage tracking, and metadata management - Monitor and tune system performance for scalability and efficiency Collaboration & Support : - Work closely with data scientists, business analysts, and product teams to deliver insights - Provide support for analytics use cases including predictive analytics, ML model integration, and experimentation pipelines Required Technical Skills : - Cloud Platforms : AWS / Azure / GCP (minimum one platform is mandatory) - Data Warehousing : Redshift, Snowflake, BigQuery, Synapse, etc. - ETL Tools : Apache Airflow, Azure Data Factory, Glue, Talend, Informatica, dbt - Programming : Python, SQL (must-have), Spark (good to have) - BI Tools : Power BI, Tableau, or similar - Data Modeling : Star/Snowflake schema, normalization, and performance tuning - Storage Technologies : S3, ADLS, GCS, relational and NoSQL databases - Version Control & CI/CD : Git, DevOps pipelines for data workflows Educational Qualifications : - Bachelors or Masters degree in Computer Science, Data Engineering, Information Systems, or related field Preferred Certifications (Nice to Have) : - AWS Certified Data Analytics Specialty (ref:hirist.tech)

Location: pune, IN

Posted Date: 4/18/2025