Senior Data Engineer (AWS)

Role Overview

We are seeking an experienced Senior Data Engineer to design, develop, and manage enterprise-grade data platforms that serve analytics, data science, and digital product needs. This role involves contributing to data architecture, defining engineering standards, and making technical decisions within a complex organizational setting.

Key Responsibilities

• Architect, develop, and sustain scalable data pipelines and data platform infrastructures to support data ingestion, transformation, and delivery processes.
• Create robust data models and develop reusable data functions catering to analysts, data scientists, and application teams.
• Enhance data platform robustness by improving reliability, security, efficiency, monitoring capabilities, and maintainability.
• Assess technologies and architectural designs, performing informed technical trade-offs while contributing to overall engineering standards.
• Promote adoption of modern engineering methodologies such as automated testing, code reviews, continuous integration and deployment (CI/CD), and Infrastructure-as-Code.
• Work collaboratively with engineering teams, product managers, data scientists, and analysts, while also providing leadership, mentoring, and knowledge exchange.

Candidate Requirements

• At least 7 years of professional experience in software or data engineering with proficient Python and SQL programming skills.
• Experience working with AWS cloud services and modern data platforms including Redshift, Snowflake, Databricks, or BigQuery.
• Expertise in enterprise data architecture and handling production data systems.
• Proven hands-on capability in designing data pipelines, data warehouses, lakes, or lakehouse systems.
• Experience in orchestrating, transforming, and modeling data effectively.
• Strong knowledge of production-grade engineering best practices including testing, CI/CD pipelines, monitoring, issue troubleshooting, and ensuring data quality.

Preferred Qualifications

• Familiarity with Apache Airflow, dbt, and/or Apache Spark technologies.
• Deep understanding of AWS data-related services and cloud infrastructure management.
• Experience with business intelligence tools such as Tableau, Power BI, or equivalents.
• Knowledge of Infrastructure-as-Code practices, and data observability, metadata management, data cataloging, or data lineage concepts.
• Experience managing sensitive or regulated datasets.