Senior Data Engineer

TALA

. Own and operate data pipelines, including Tala's change data capture (CDC) and data synchronization infrastructure .

Posted 11/4/2026full-timeRemote • United StatesSenior💰 $130,000 - $200,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and optimizing data pipelines, ensuring data accuracy and performance while leveraging cloud infrastructure and modern data architectures. Proficient in Python, Apache Spark, and CI/CD practices to support scalable data solutions.

Highest-signal resume keywords

Data Pipeline DevelopmentPython ProgrammingApache Spark ProficiencyAWS Cloud InfrastructureInfrastructure-as-Code

ATS Keywords

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Hard Skills

Data EngineeringChange Data CaptureStream ProcessingDatabase ManagementDistributed SystemsLarge-Scale Data ProcessingUnit TestingIntegration TestingMonitoring and AlertingSchema Evolution

Soft Skills

Effective CommunicationCollaboration

Tools & Technologies

SnowflakeApache KafkaTerraformJenkinsAirflowAmazon EMRAmazon S3Amazon RDSKubernetesApache Iceberg

Industry Keywords

Data LakehouseCI/CD WorkflowsService Level ObjectivesProduction-Grade PipelinesTechnical Design Documentation

Tech Stack

Tools & technologies

AirflowApacheAWSCloudDistributed SystemsJenkinsKafkaKubernetesMySQLPostgresPythonSnowflakeSparkTerraform

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

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