Senior Data Engineer

- Write and defend diagnostic SQL queries against large-scale production datasets

- Build and maintain ingestion pipelines for bid, win, and impression logs into BigQuery

- Harmonize fields across independently designed datasets and maintain versioned field mappings

- Develop point-in-time-correct feature tables and aggregation pipelines

- Design and maintain conversion and labeling pipelines with delayed label handling

- Own the data serving write path, schema contracts, publishing flows, and freshness SLOs

- Build experimentation infrastructure including traffic splitting and reporting pipelines

- Perform large-scale historical backfills and safe reprocessing after mapping changes

- Implement data isolation and safe-aggregation controls for advertiser data protection

- Develop automated data quality validation frameworks

- Collaborate closely with Customer engineers and prepare operational documentation

- Contribute to architecture discussions and platform scalability improvements

- 5+ years of experience in Data Engineering

- At least 2 years of experience working with production ML or large-scale analytics pipelines

- Expert-level SQL skills including window functions and incremental processing patterns

- Strong Python skills for production-grade pipeline development

- Hands-on experience with Spark or PySpark

- Experience designing ETL / ELT pipelines with Airflow, Cloud Composer, Dagster, or similar tools

- Experience working with cloud data warehouses at scale, preferably BigQuery

- Strong understanding of data modeling and point-in-time correctness

- Experience working with event-driven or clickstream datasets at very large scale

- Experience supporting business-critical production pipelines

- Upper-Intermediate English level or higher

WILL BE A PLUS

- Experience with GCP services including Dataflow, Pub/Sub, GCS, and Beam

- Experience building streaming or near-real-time ingestion systems

- Understanding of feature stores, train/serve skew, and label leakage prevention

- Experience in AdTech or auction-based environments

- Experience handling delayed or incomplete labels in ML systems

- Experience with dbt or similar transformation frameworks

- Experience delivering solutions into Customer-owned infrastructure

- Knowledge of GDPR/CCPA-related privacy engineering practices

- Experience with experimentation infrastructure and statistical validation pipelines

- Experience working in hybrid cloud/on-prem Linux environments

- Terraform and Kubernetes experience

- Experience optimizing warehouse cost and performance

PERSONAL PROFILE

- Strong analytical and problem-solving skills

- Ownership-oriented mindset

- Ability to work independently in a client-facing environment

- Strong communication and documentation skills

- Comfortable working in a fast-paced engineering environment

- Collaborative and proactive attitude

Join Sigma Software to build large-scale data infrastructure powering a real-time AdTech platform processing hundreds of millions of auction requests daily. We are looking for a Senior Data Engineer who enjoys solving complex distributed data challenges and building production-grade ML-oriented data systems.

You will become part of a dedicated Sigma Software team developing predictive modeling and optimization capabilities for a live advertising ecosystem. The role combines large-scale event processing, streaming and batch pipelines, experimentation infrastructure, and high-throughput data engineering in a cloud-native environment.

We as a company offer the opportunity to work on impactful global products, collaborate with experienced engineers, and contribute to architecture decisions while growing your expertise in large-scale distributed systems and modern data platforms.
CUSTOMER

Our Customer is a technology company operating supply-side infrastructure within the programmatic advertising ecosystem. The company manages a large-scale ad exchange handling hundreds