Senior Software Engineer

What You'll Do

• Design, build, and operate large-scale data acquisition pipelines that ingest, validate, transform, enrich, and store high-volume raw data.
• Architect resilient ETL/ELT workflows for batch, streaming, scheduled, and event-driven data processing.
• Develop production Java services and data processing applications for ingestion, orchestration, enrichment, deduplication, and delivery.
• Build and improve systems using technologies such as Apache Airflow, Apache Beam, Spark, Google Dataflow, DataProc, Kafka, and Pub/Sub.
• Define practical approaches for schema evolution, data contracts, data validation, backfills, replayability, and idempotent processing.
• Improve reliability, performance, scalability, and cost efficiency across data acquisition pipelines and services.
• Implement observability, monitoring, and alerting for pipeline health, throughput, latency, failure rates, and data quality metrics.
• Work with product, data science, platform, and data quality teams to translate business needs into production-ready systems.
• Contribute to technical designs, implementation plans, and system modernization efforts across Data Acquisition.

Must-Have Qualifications

Data Engineering and Pipelines

• 5+ years of professional software engineering experience with a strong focus on backend systems, data engineering, or distributed processing.
• Proven experience building and operating production data pipelines at scale.
• Deep proficiency with Java and object-oriented design.
• Hands-on expertise with data processing and orchestration technologies such as Apache Beam, Apache Airflow, Spark, Google Dataflow, or DataProc.
• Strong experience with streaming systems such as Apache Kafka, Google Pub/Sub, or similar technologies.
• Strong understanding of batch processing, streaming processing, data modeling, schema evolution, and data quality management.
• Experience designing ETL/ELT workflows that process large volumes of structured and semi-structured data.

Backend and Distributed Systems

• Experience designing high-throughput, fault-tolerant backend services and distributed systems.
• Strong understanding of APIs, integration patterns, retries, backpressure, idempotency, and operational failure modes.
• Ability to write clean, maintainable production code and evaluate tradeoffs in system design.
• Experience with large-scale storage and query technologies such as BigQuery, Snowflake, Trino, or similar systems.

Cloud and Operations

• Experience with at least one cloud provider, preferably GCP.
• Hands-on experience with cloud services such as BigQuery, GCS, GKE, Dataflow, DataProc, and Pub/Sub.
• Experience operating production services with monitoring, logging, alerting, SLIs, and incident investigation.
• Ability to analyze and improve pipeline performance, reliability, resource utilization, and cost.

General

• Bachelor's degree in Computer Science, Software Engineering, or a related field.
• Ability to translate business and data requirements into clear technical designs and implementation plans.
• Pragmatic engineering judgment with the ability to balance correctness, delivery speed, maintainability, and operational risk.

Nice to Have

• Experience with Kubernetes, especially GKE or EKS, for running distributed workloads.
• Experience with Terraform or other infrastructure-as-code tools.
• Experience with Snowflake, BigQuery, Starburst/Trino, or similar query engines.
• Knowledge of data integration patterns involving CRM systems, email/calendar APIs, third-party feeds, change data capture, or external data providers.
• Experience in a B2B data company, data marketplace, or data-as-a-product environment.
• Expert-level experience with Apache Spark or another distributed processing framework.