Senior Data Engineer

Syndesus, Inc.; San Francisco (CA); On-site; USD 180,000 - 260,000; Full time

Benefits offered by this job

Bonus

Pension

Medical/dental/vision

Generous PTO

Paid parental leave

Job summary

Syndesus, Inc. is a well-established consumer software company with a large global footprint. We seek a Senior IC to design, build, and operate data architecture powering analytics, ML/AI, and BI across our platform.

You will bridge data engineering, data science, and data quality, partnering with stakeholders, data scientists, and product teams to deliver scalable data solutions.

Qualifications

• 8+ years of ETL/ELT pipeline development across varied data sources.
• Proficient in Python, Scala, or Java (production-quality code).
• Experience with Snowflake, Databricks, Spark, Kafka, and Airflow.
• Cloud experience (AWS/Azure/GCP) and native data services.
• Experience with real-time data processing and streaming architectures.
• Strong data modeling and warehousing fundamentals.
• Knowledge of Docker and Kubernetes.
• Familiar with MCP and AI-assisted development tools.
• Data governance and PII handling experience.
• Strong communication across technical and non-technical stakeholders.

Responsibilities

• Design and deploy comprehensive data architecture capturing structured and unstructured data from diverse internal and external sources.
• Build resilient ETL/ELT pipelines routing data across cloud structures, local databases, and other storage forms.
• Implement data quality frameworks — validation, monitoring, and automated recovery strategies.
• Collaborate with data scientists to enable advanced analytics, predictive modeling, and ML initiatives.
• Develop web-enabled, self-service analytics solutions that democratize data access company-wide.
• Apply AI/ML and big-data techniques to automate data cleansing, transformation, and enrichment.
• Leverage MCP (Model Context Protocol) to connect enterprise applications and automate data flows.
• Ensure secure, scalable, and compliant data ingestion with appropriate PII handling.
• Troubleshoot pipeline issues, optimize performance, and participate in on-call rotations.
• Mentor junior team members and contribute to data engineering practice growth.

Skills

Python

Scala

Java

Snowflake

Databricks

Apache Spark

Kafka

Airflow

AWS

Azure

GCP

Real-time processing

Data modeling

Data warehousing

Dimensional modeling

Docker

Kubernetes

MCP

AI tools

DataOps

MLOps

PII handling

Communication

Tools

Docker

Kubernetes

Snowflake

Databricks

Apache Spark

Kafka

Airflow

AWS

Azure

GCP

Job description

The Company

Well-established consumer software company with a large global footprint. Strong benefits: bonus, pension, medical/dental/vision, generous PTO, and paid parental leave.

The Role

Senior IC role on a data innovation team responsible for designing, building, and operating the data architecture that powers analytics, ML/AI initiatives, and business intelligence across a large-scale consumer software platform. You'll work at the intersection of data engineering, data science, and data quality — partnering closely with stakeholders, data scientists, and product teams.

Responsibilities

• Design and deploy comprehensive data architecture capturing structured and unstructured data from diverse internal and external sources
• Build resilient ETL/ELT pipelines routing data across cloud structures, local databases, and other storage forms
• Implement data quality frameworks — validation, monitoring, and automated recovery strategies
• Collaborate with data scientists to enable advanced analytics, predictive modeling, and ML initiatives
• Develop web-enabled, self-service analytics solutions that democratize data access company-wide
• Apply AI/ML and big-data techniques to automate data cleansing, transformation, and enrichment
• Leverage MCP (Model Context Protocol) to connect enterprise applications and automate data flows
• Ensure secure, scalable, and compliant data ingestion with appropriate PII handling
• Troubleshoot pipeline issues, optimize performance, and participate in on-call rotations
• Mentor junior team members and contribute to data engineering practice growth

Requirements

• 8+ years of hands-on ETL/ELT pipeline development across varied data sources
• Strong programming skills in Python, Scala, or Java (production-quality code)
• Experience with modern data platforms — Snowflake, Databricks, Apache Spark, Kafka, Airflow
• Cloud platform experience — AWS, Azure, or GCP and their native data services
• Experience with real-time data processing and streaming architectures
• Solid data modeling, warehousing, and dimensional modeling fundamentals
• Knowledge of containerization and orchestration (Docker, Kubernetes)
• Practical knowledge of MCP and AI-assisted development toolsFamiliarity with DataOps and MLOps practices
• Experience managing sensitive/PII data with attention to compliance and governance
• Strong communication skills across technical and non-technical stakeholders

Preferred

• Background in data science or analytics
• Experience in client-facing or Professional Services roles