Senior Data Engineer

Job Summary

This position will lead the design, evaluation, implementation, and testing of a scalable, high-performance enterprise data warehouse. In this role, you will be responsible for developing dimensional data models, ETL/ELT pipelines, and cloud-based data solutions that enable robust analytics and reporting. You will collaborate with cross‑functional teams to ensure data quality, governance, and security while optimizing performance for large-scale datasets. The ideal candidate has a strong background in SQL, cloud data platforms (AWS, GCP, or Azure), and data pipeline automation and is enthusiastic about building modern data architectures and enabling data-driven decision‑making.

• Data Warehouse Design & Architecture
  • Lead the end-to-end design and implementation of a scalable, high-performance data warehouse.
  • Define data architecture principles, strategies, and best practices to ensure optimal performance and maintainability.
• Dimensional Modeling & Data Modeling
  • Design and implement robust dimensional models (star and snowflake schemas) to optimize analytical queries.
  • Develop conceptual, logical, and physical data models to support reporting, analytics, and business intelligence.
  • Ensure data models align with business requirements and support self‑service analytics.
  • Leverage existing data infrastructure to fulfill all data‑related requests, perform necessary data housekeeping, data cleansing, normalization, hashing, and implementation of required data model changes.
• ETL/ELT Development & Data Pipelines
  • Design, develop, and optimize ETL/ELT pipelines to ingest, transform, and load structured and unstructured data from various sources.
  • Ensure data pipelines are scalable, efficient, and maintainable while handling large datasets.
  • Implement incremental data processing strategies to manage real‑time and batch workloads.
• Data Governance, Quality, and Security
  • Establish data governance practices, including data cataloging, lineage tracking, and metadata management.
  • Implement data validation, anomaly detection, and quality monitoring to ensure accuracy and consistency.
  • Collaborate with security teams to enforce role‑based access control (RBAC), encryption, and compliance standards (GDPR, HIPAA, etc.).
• Performance Tuning & Optimization
  • Optimize database performance by indexing, partitioning, caching, and query tuning.
  • Monitor and troubleshoot slow queries, ensuring efficient use of resources.
  • Analyze data to spot anomalies, trends and correlate similar data sets.
• Cloud Technologies
  • Architect and implement cloud-based data warehouse solutions (e.g., Snowflake, AWS Redshift, Google Big Query, Azure Synapse).
• Collaboration & Cross‑Functional Work
  • Work closely with business stakeholders & analysts to translate requirements into scalable data solutions.
  • Partner with software engineers and Dev Ops teams to ensure seamless data integration and infrastructure reliability.
• Monitoring & Incident Response
  • Establish monitoring solutions for data pipeline failures, schema changes, and data anomalies.
  • Set up logging and alerting mechanisms to proactively identify and resolve issues.
• Mentorship & Best Practices
  • Guide and mentor other members of the data team on best practices in data modeling, ETL, and architecture.
  • Define and document standards for data warehouse development, maintenance, and governance.
• Data Science & Machine Learning
  • Design, develop, and implement statistical models to carry out various novel aspects of classification and information extraction from data.
  • Design, develop, and implement natural language processing software modules.

• Bachelor’s degree and 6+ years of experience in data analytics, data engineering, data architecture, or software engineering with a focus on data warehouse design and implementation.
• Proven experience designing and implementing dimensional data models (star schema, snowflake schema) for enterprise‑scale data warehouses.
• Hands‑on experience with ETL/ELT development using tools like dbt, Informatica, Talend, Apache Airflow, or custom data pipelines.
• 3+ years of experience working with cloud-based…