Principal Engineer – Software

This is a fully remote position, open to applicants in India.

📋 Description

• Conduct technical feasibility assessments and evaluate solutions for data and analytics projects based on business, operational, and regulatory requirements.

• Spearhead the design and execution of scalable data engineering solutions, encompassing data pipelines, data models, data integrations, and analytics-ready data products.

• Provide technical guidance for data architecture, ETL/ELT design, code assessments, performance optimization, production support, and troubleshooting.

• Drive the modernization of outdated data and reporting systems, facilitating transitions from traditional ETL and reporting tools to contemporary cloud data platforms and transformation frameworks.

• Design and manage data pipelines utilizing cloud technologies, Python, Spark, SQL, and associated orchestration and transformation tools.

• Support enterprise analytics platforms, which include data warehouses, reporting, semantic layers, and business intelligence environments.

• Collaborate with stakeholders to outline and implement the technical roadmap for data engineering, analytics enablement, platform modernization, data quality, and automation.

• Establish and advocate for engineering standards, reusable patterns, coding guidelines, testing methodologies, data quality controls, and documentation standards.

• Work alongside architecture, security, infrastructure, governance, and business teams to ensure data solutions are secure, dependable, scalable, and in line with enterprise standards.

• Mentor engineers and technical team members, fostering skill enhancement in cloud data engineering, data modeling, analytics engineering, and contemporary data platform practices.

• Contribute to AI/ML enablement by guaranteeing that data pipelines, curated datasets, and feature-ready data assets are reliable, governed, and appropriate for advanced analytics and machine learning applications.

• Remain updated on the latest trends in data engineering, cloud computing, analytics, AI/ML, and automation to promote continuous enhancement and technical innovation.

⛳️ Requirements

• Bachelor’s degree in computer science, information systems, data engineering, analytics, engineering, or equivalent training and experience.

• Over 12 years of experience in software engineering, data engineering, analytics engineering, or the development of enterprise data platforms.

• Demonstrated experience in designing, developing, and maintaining intricate data solutions involving multiple systems, stakeholders, business domains, and production dependencies.

• Strong proficiency with Python, SQL, distributed data processing, and ETL/ELT development; experience with Spark or similar large-scale data processing frameworks is highly preferred.

• Familiarity with cloud-based data platforms and services, preferably AWS, including the development, deployment, monitoring, and operational support of data solutions.

• Experience with enterprise data warehouses, data marts, reporting platforms, and business intelligence solutions; knowledge of platforms such as Redshift, Snowflake, SAP BusinessObjects Data Services, SAP Web Intelligence, or similar technologies is preferred.

• Experience with contemporary data transformation and analytics engineering tools such as dbt or equivalent frameworks is preferred.

• Strong understanding of data modeling, data warehousing, data quality, metadata management, data lineage, performance optimization, and production support practices.

• Working knowledge of AI/ML concepts and the data engineering methodologies required to support advanced analytics, machine learning, and model-ready datasets.

• Proven capability to design data solutions that integrate with both internal and external systems while adhering to security, governance, scalability, and reliability standards.

• In-depth understanding of software development and data engineering practices in a distributed team environment, including version control, testing, CI/CD, release management, and operational monitoring.

• Exceptional problem-solving, analytical, communication, and stakeholder management abilities.

• Proven team player with the capacity to mentor technical team members and influence engineering direction across teams.

• Certifications in cloud, data engineering, data architecture, analytics engineering, or AI/ML are preferred.

🏝️ Benefits

• Flexible work environment.

• Strong emphasis on work-life balance.

• Opportunities for internal mobility and career advancement.

• Inclusive workplace culture.

• Volunteering opportunities.