Remote Senior Data Engineer
Oportun
πRemote - India
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Job highlights
Summary
Join Oportun's team as a Sr. Data Engineer and contribute to designing, developing, and maintaining sophisticated software/data platforms. As a key member of our engineering group, you will lead technical requirements gathering, mentor junior engineers, and collaborate with cross-functional teams to deliver high-quality, scalable software solutions.
Requirements
- Bachelor's or Master's degree in Computer Science, Data Science, or a related field
- 5+ years of experience in data engineering, with a focus on data architecture, ETL, and database management
- Proficiency in programming languages like Python/PySpark and Java or Scala
- Expertise in big data technologies such as Hadoop, Spark, Kafka, etc
- In-depth knowledge of SQL and experience with various database technologies (e.g., PostgreSQL, MariaDB, NoSQL databases)
- Experience and expertise in building complex end-to-end data pipelines
- Ability to work in an Agile environment (Scrum, Lean, Kanban, etc)
- Ability to mentor junior team members
- Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and their data services (e.g., AWS Redshift, S3, Azure SQL Data Warehouse)
- Strong leadership, problem-solving, and decision-making skills
- Excellent communication and collaboration abilities
Responsibilities
- Lead the design and implementation of scalable, efficient, and robust data architectures to meet business needs and analytical requirements
- Collaborate with stakeholders to understand data requirements, build subject matter expertise, and define optimal data models and structures
- Design and develop data pipelines, ETL processes, and data integration solutions for ingesting, processing, and transforming large volumes of structured and unstructured data
- Optimize data pipelines for performance, reliability, and scalability
- Oversee the management and maintenance of databases, data warehouses, and data lakes to ensure high performance, data integrity, and security
- Implement and manage ETL processes for efficient data loading and retrieval
- Establish and enforce data quality standards, validation rules, and data governance practices to ensure data accuracy, consistency, and compliance with regulations
- Drive initiatives to improve data quality and documentation of data assets
- Provide technical leadership and mentorship to junior team members, assisting in their skill development and growth
- Lead and participate in code reviews, ensuring best practices and high-quality code
- Collaborate with cross-functional teams, including data scientists, analysts, and business stakeholders, to understand their data needs and deliver solutions that meet those needs
- Communicate effectively with non-technical stakeholders to translate technical concepts into actionable insights and business value
- Implement monitoring systems and practices to track data pipeline performance, identify bottlenecks, and optimize for improved efficiency and scalability
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