Senior Data Engineer

🔥 12 hours ago

🇺🇸 United States – Remote

💵 $130k - $200k / year

⏰ Full Time

🟠 Senior

🚰 Data Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

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Tala

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2011

💳 Fintech

🤖 Artificial Intelligence

👥 B2C

Fintech • Artificial Intelligence • B2C

Tala is a fintech company that aims to break down financial barriers for individuals across Kenya, Mexico, the Philippines, and India through its innovative money app. The company provides a suite of financial services, including credit, payments, savings, and transfers, to empower their customers. Leveraging advanced artificial intelligence and machine learning technologies, Tala offers personalized financial experiences and creates digital financial identities for users who have been underserved by traditional finance institutions. With a focus on real-time money management, Tala's app simplifies access to instant credit and other financial services for millions, enhancing users' economic power and quality of life.

📋 Description

• Own and operate data pipelines, including Tala's change data capture (CDC) and data synchronization infrastructure • Ensure accurate and timely delivery of data from market-level databases into Snowflake • Improve pipeline performance and scalability, reduce latency, optimize infrastructure costs, and support growing data volumes • Onboard new data sources, tables, and markets while managing schema evolution and system compatibility • Establish service level objectives (SLOs), implement monitoring and alerting, and build automated data quality checks • Develop and maintain unit and integration tests, CI/CD workflows, infrastructure-as-code, and safe deployment strategies, including dry runs and blue-green deployments • Troubleshoot production issues, conduct root cause analyses, and improve monitoring, testing, documentation, and operational runbooks • Participate in architecture and design discussions, write and review technical design documents, and provide code review feedback • Collaborate with Data Science, Analytics, Data Platform, Product, Credit, and Business Development teams

🎯 Requirements

• 4+ years of experience in backend engineering or data engineering, ideally supporting consumer-scale applications • At least 2 years of hands-on professional Python experience • Proven experience independently building, operating, and improving production-grade data pipelines • Hands-on experience with change data capture (CDC) and stream processing technologies such as Kafka, Amazon MSK, AWS DMS, or comparable tools • Strong proficiency in Apache Spark, particularly Spark Structured Streaming • Experience with modern data lakehouse architectures and table formats such as Apache Iceberg, Delta Lake, or Apache Hudi, as well as Parquet • Strong database experience across relational and analytical systems, including MySQL, PostgreSQL, Amazon RDS, and Snowflake • Hands-on experience with AWS cloud infrastructure, ideally including EMR, S3, MSK, DMS, RDS, and EKS • Experience with infrastructure-as-code and CI/CD tools such as Terraform, Terragrunt, Helm, and Jenkins • Familiarity with pipeline orchestration and job scheduling tools such as Airflow or Python-based services running on Kubernetes • Strong understanding of distributed systems, scalable algorithms, and large-scale data processing • Ability to communicate complex technical concepts clearly and collaborate effectively with engineering teams and business stakeholders • Nice to have: Experience with Trino or Presto • Nice to have: Experience with Kubernetes and containerized applications • Nice to have: Familiarity with AWS Glue • Nice to have: Experience with additional stream processing technologies such as Debezium, Amazon Kinesis, or Apache Flink • Nice to have: Experience with other modern data lakehouse technologies such as Delta Lake or Apache Hudi • Nice to have: Advanced degree in Computer Science, Mathematics, or a related technical field

🏖️ Benefits

• Remote-first approach • Office hubs in Santa Monica, CA (HQ); Nairobi, Kenya; Mexico City, Mexico; Manila, the Philippines; and Bangalore, India

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