Job location:
Remote India
About the role:
The Data Engineering team is seeking a Data Engineer with expertise in data infrastructure, pipeline development, and scalable data solutions to play a pivotal role in enabling data-driven decision-making across the organization. The successful candidate will have a deep knowledge of data architecture and engineering best practices, and will work closely with cross-functional teams to ensure data is clean, reliable, and accessible. This role requires strong technical skills, a solid grasp of business needs, and the ability to bridge the gap between raw data and actionable insights through robust engineering solutions.
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ETL/ELT Pipeline Development: Build, and maintain scalable data pipelines using AWS. Implement both batch and incremental load patterns for BI reporting and application data needs.
- Real-Time Data Streaming: Develop and manage real-time data ingestion pipelines using Kafka. Ensure low-latency, fault-tolerant data flow for critical business workflows.
- Workflow Orchestration: Build, schedule, and monitor end-to-end data workflows using Apache Airflow. Manage dependencies, retries, and alerting for production DAGs.
- Data Warehouse Management: Administer and optimize Amazon Redshift clusters including schema design, query performance tuning, distribution/sort keys, and vacuuming to ensure high availability and cost efficiency.
- Data Quality & Observability: Implement automated data quality checks at ingestion and transformation stages. Define validation rules, build alerting for anomalies and discrepancies, and establish SLAs to ensure stakeholders can trust the data they use.
- API Integrations: Integrate third-party and internal REST APIs into data pipelines to pull operational and product data into the warehouse.
- Cloud Cost Optimization: Monitor and right-size data processing and storage resources across S3, EMR, Redshift, EC2, and Lambda. Proactively identify inefficiencies and propose cost-saving improvements.
- BI & Analytics Collaboration: Partner with the BI team to align data models, preprocessing logic, and Redshift schema design with reporting and dashboard needs.
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Bachelor’s degree in Computer Science or a related quantitative field.
- 2+ years of experience working as a Data Engineer
- Good proficiency in Python and SQL for data transformation and pipeline development
- Hands-on experience with Apache Spark (PySpark) for large-scale data processing
- Working knowledge of Kafka for real-time data ingestion and stream processing
- Hands-on experience managing and maintaining Airflow DAGs in production environments
- Familiarity with Redshift performance tuning, schema design, and query optimization
- Experience implementing automated data validation and quality checks within pipelines
- Detail-oriented with a keen interest in data transformations and their impact on business outcomes
- Problem-solving and time management skills
- Prior experience in project or team management is preferred, enthusiasm for mentoring and guiding others is a plus.
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Professional growth in a dynamic, rapidly expanding, high-social-impact industry
- An open-minded, collaborative culture made up of enthusiastic colleagues who are driven by the challenge of innovation towards profound impact on people and the planet.
- A truly multicultural experience: you will have the chance to work with and learn from people from different geographies, nationalities, and backgrounds.
- Structured, tailored learning and development programs that help you become a better leader, manager, and professional through the Sun King Center for Leadership.
Sun King is the world’s leading off-grid solar energy company, combining cutting-edge product design, fintech, and field operations to deliver energy access for the 1.8 billion people who live without an affordable and reliable electric-grid connection.
Sun King has built a new kind of energy utility: distributed, green, customer-centric, and affordable. We bring clean, reliable, decentralized energy directly into people’s lives — from solar kits that provide first-time energy access to multi-kilowatt systems that serve both off-grid users and grid-connected customers powering larger homes, schools, hospitals, farms, offices, and light manufacturing.
Already, 25 million homes and businesses rely on Sun King for electricity supply and the appliances and services it enables: lighting, televisions, fans, refrigeration, and smartphones.
Sun King combines energy generation, energy-efficient appliances, installation, and financing into one seamless offering. Think of it as a distributed utility, designed for wherever energy is needed and designed to scale with its users as incomes and energy needs grow.
Sun King makes solar products affordable to low-income households and businesses via ‘pay-as-you-go’ (PAYG) purchase financing. Sun King installs solar after customers pay a small deposit. Customers then make small, manageable payments of as little as US $0.14 a day via mobile money or cash.
Instead of paying for expensive, polluting, and health-damaging kerosene for lighting or diesel for power, customers unlock savings through accessing solar power and after one to two years of payments, customers own their solar equipment outright.
Sun King collects payments digitally through mobile money systems and its 35,000 field agents — over 1 million payments each day. To date, Sun King has extended more than $1.4 billion in PAYG loans to customers.
Sun King began by powering homes and businesses with solar systems delivered through PAYG financing. Now, we’re using the same model to make smartphones and clean cooking equipment affordable: helping households connect to the digital economy and transition from wood-based fuels to modern, sustainable alternatives.
Sun King employs 3,500 full-time staff in 14 countries, with specialties spanning product design, data science, logistics, customer service, sales, software, operations, and more — all with a passion to serve off-grid families. Sun King is committed to gender diversity in the workplace. Women represent 42% of Sun King’s workforce.
