Data Engineer I

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

📋 Description

• Design and implement scalable, secure, and reliable data pipelines utilizing modern data platforms such as Spark, Databricks, Airflow, and Snowflake.

• Create ETL/ELT processes to ingest data from both structured and unstructured sources.

• Conduct Exploratory Data Analysis to identify trends, validate data integrity, and generate insights for data product development and business decision-making.

• Collaborate with data scientists, analysts, and software engineers to create data models that support high-quality analytics and real-time insights.

• Write maintainable Python code accompanied by thorough unit and integration tests.

• Take ownership of end-to-end feature delivery within an agile, collaborative setting.

• Lead complex data and trend analyses in partnership with data science, product, engineering, and customer success teams.

• Benchmark and evaluate product operations projects; develop and disseminate scorecards and reports.

• Identify and pursue new opportunities informed by customer and business data.

• Contribute to the development of policies, processes, and tools that address challenges related to product quality.

⛳️ Requirements

• A Bachelor's or Master's degree in Computer Science, Engineering, or a related discipline.

• Over 2 years of practical experience in data engineering or backend software development positions.

• Strong grasp of Relational Databases (RDS, MySQL, PostgreSQL).

• Experience with Apache Kafka or RabbitMQ for constructing asynchronous, decoupled systems.

• Proficient in Python, SQL, and at least one data pipeline orchestration tool (e.g., Apache Airflow, Luigi, Prefect).

• Extensive experience with cloud-based data platforms (e.g., AWS Redshift, GCP BigQuery, Snowflake, Databricks).

• In-depth understanding of data modeling, data warehousing, and distributed systems.

• Familiarity with DevOps practices (CI/CD, infrastructure as code, containerization using Docker/Kubernetes).

• Exposure to AI/ML-integrated solutions or a keen interest in collaborating with data science teams.

• Awareness of data security and privacy regulations (e.g., GDPR, HIPAA).

• Understanding of prompt engineering and the interaction of LLM-based systems with data.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance.

• Flexible work hours and remote work options.

• Opportunities for professional development and continuous learning.

• Dynamic and inclusive company culture.