Senior ETL Engineer at DigiCert Inc

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

13 May, 26

Salary

0.0

Posted On

12 Feb, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

ETL Development, SQL, Python, Databricks, Spark, PySpark, Cloud Data Platforms, Data Warehousing, Dimensional Modeling, Data Design, Data Quality, Analytics, Problem-Solving, Collaboration, Mentoring, Agile

Industry

Computer and Network Security

Description

Who we are DigiCert is a global leader in intelligent trust, helping organizations protect the digital interactions people rely on every day. From websites and cloud services to connected devices and critical systems, we make sure digital experiences are secure, private, and authentic. Our AI-powered DigiCert ONE platform brings together certificates, DNS, and lifecycle management to help organizations stay ahead of risk as technology and threats evolve. Trusted by more than 100,000 organizations—including 90% of the Fortune 500—DigiCert helps businesses operate with confidence today while preparing for what’s next, including a quantum-safe future. Job summary We are looking for a Senior ETL Engineer to design, build, and maintain scalable data pipelines that power analytics, reporting, and data-driven decision making across the organization. This role requires strong SQL and Python expertise, hands-on Databricks experience, and a deep understanding of data and how it is used to drive analytics and insights. You will work closely with data engineers, analytics teams, and business stakeholders to ensure high-quality, reliable, and well-modeled data that elevates our analytics capabilities. What you will do Design, develop, and maintain robust ETL/ELT pipelines using SQL and Python, working with large-scale datasets Build scalable and maintainable data workflows leveraging Spark / PySpark and cloud-based data platforms Translate business and analytical requirements into high-quality, well-structured datasets Apply strong data modeling and data design principles to support downstream analytics and reporting Optimize data pipelines for performance, reliability, and cost efficiency Ensure data quality, accuracy, and consistency through validation, testing, and monitoring Partner closely with analytics and BI teams to enable trusted, analytics-ready data Collaborate with analytics teams on reporting and dashboard needs to ensure data accuracy, correctness, and performance Troubleshoot and resolve data pipeline failures and data issues end-to-end Contribute to architectural decisions, best practices, and data engineering standards Participate in code reviews, technical design discussions, and platform improvements Mentor junior engineers and help elevate overall data engineering practices Document data pipelines, workflows, and operational processes What you will have 5+ years of experience in data engineering, ETL development, or a related role Strong proficiency in SQL and Python, with hands-on experience building production-grade ETL pipelines using both Hands-on experience with Databricks, Spark, and PySpark Experience working with cloud data platforms (AWS, Azure, or GCP) Strong understanding of data warehousing concepts, dimensional modeling, and analytics-friendly data design A strong sense of data and how it supports analytics, reporting, and business insights Experience building batch and incremental data pipelines Familiarity with Git, version control, and CI/CD practices Strong problem-solving skills and ability to work independently on complex data challenges Clear communication skills and ability to collaborate across engineering and analytics teams Nice to have Experience with streaming or near real-time data pipelines (Kafka, Kinesis, etc.) Familiarity with data quality, observability, and monitoring tools Experience supporting BI tools and analytics use cases Exposure to machine learning pipelines or feature engineering Prior experience mentoring or guiding junior engineers Experience working in Agile or Scrum environments Benefits Generous time off policies Top shelf benefits Education, wellness and lifestyle support #LI-SS1

Responsibilities

Design, develop, and maintain robust ETL/ELT pipelines using SQL and Python, while ensuring high-quality, reliable data for analytics. Collaborate with analytics teams to troubleshoot data issues and contribute to architectural decisions.