Job Summary

• We are seeking an experienced Senior Data Engineer to design, build, and maintain scalable data infrastructure that supports analytics, reporting, and data-driven decision-making.
• The ideal candidate will play a key role in architecting reliable data pipelines, optimizing data systems, and ensuring high data quality across the organization while collaborating closely with analytics, product, and engineering teams.

Key Responsibilities

• Design, build, and maintain scalable and reliable data pipelines (ETL/ELT)
• Develop and manage data architectures including data lakes, warehouses, and streaming systems
• Ensure data quality, integrity, security, and governance across all data systems
• Optimize data processing performance and reliability for large datasets
• Collaborate with product, analytics, and engineering teams to understand data requirements
• Implement monitoring, alerting, and logging for data pipelines
• Lead code reviews and enforce data engineering best practices
• Mentor junior data engineers and provide technical leadership
• Document data models, pipelines, and system architectures
• Troubleshoot and resolve complex data-related production issues

Required Qualifications & Experience

• Bachelor’s Degree in Computer Science, Engineering, Mathematics, or a related field
• 5+ years of professional experience in data engineering or backend data roles
• Strong proficiency in SQL and data modeling
• Hands-on experience with Python, Java, or Scala for data processing
• Experience building ETL/ELT pipelines using tools such as Airflow, dbt, or similar
• Solid experience with data warehouses (BigQuery, Snowflake, Redshift, PostgreSQL, etc.)
• Experience working with large-scale data systems and distributed processing frameworks (Spark, Flink, etc.)
• Familiarity with cloud platforms (AWS, GCP, or Azure)
• Experience with version control systems (Git)

Preferred / Nice-to-Have Skills:

• Experience with real-time/streaming data (Kafka, Kinesis, Pub/Sub)
• Knowledge of data governance, privacy, and security best practices
• Experience with containerization and orchestration (Docker, Kubernetes)
• Exposure to BI and analytics tools (Looker, Power BI, Tableau, etc.)
• Experience in FinTech, SaaS, or high-volume data environments
• Familiarity with machine learning data pipelines

Soft Skills & Competencies:

• Strong analytical and problem-solving skills
• Excellent communication and stakeholder collaboration abilities
• Ability to work independently and take ownership of data systems
• Leadership mindset with mentoring experience
• High attention to detail and commitment to data reliability and quality.