Senior Data Engineer

About SERHANT.  SERHANT. is the most followed real estate brand in the world, calibrated for the marketplace of tomorrow, delivering proven results for buyers, sellers, and developers. SERHANT. revolutionizes the traditional brokerage model by innovating through media and content creation and is powered by a full-service in-house film studio as well as an amplification platform that puts our properties in front of more people than anyone else.    About the Role  We’re looking for a Senior Data Engineer who builds data infrastructure with velocity and precision. You’ll design pipelines, architect lakehouse solutions, and create the foundation that powers our products—leveraging modern AI tools to move faster without sacrificing quality. You bring deep experience with ClickHouse, open-source data tooling, and modern lakehouse patterns.    Our Stack  Analytics Database: ClickHouse  Primary Database: Postgres  Languages: Python, TypeScript  Infrastructure: Azure, event-driven architecture    Responsibilities  Design and implement lakehouse architecture using open-source technologies  Build and optimize ClickHouse deployments for high-performance analytical workloads  Develop custom data transforms and ETL/ELT pipelines using well-supported open-source tools  Create data models that bridge our Postgres application databases with ClickHouse analytics layer  Partner with product and engineering to define data models that serve both analytical and operational needs  Write specifications before writing code—defining contracts, schemas, and expected behaviors upfront  Use AI-assisted coding tools daily to accelerate development and reduce toil  Establish data quality frameworks and observability across the pipeline  Optimize for performance, cost, and reliability at scale  *The company reserves the right to add or change duties at any time.    Qualifications  5+ years of experience in data engineering, analytics engineering, or related roles  Deep expertise with ClickHouse - deployment, optimization, schema design, and materialized views  Strong experience with Postgres and understanding of when to leverage transactional vs. analytical databases  Strong experience with lakehouse architecture patterns (Delta Lake, Apache Iceberg, Apache Hudi)  Proficiency building ETL/ELT pipelines with open-source tools (Airflow, Dagster, dbt, Prefect, or similar)  Hands-on experience with streaming and batch processing frameworks (Kafka, Flink, Spark)  Strong SQL and deep proficiency in Python  TypeScript proficiency for integration with application services  Demonstrated fluency with AI coding assistants (Cursor, Copilot, Claude, etc.) as part of your daily workflow  Experience using LLMs for data transformation, validation, or pipeline generation  A spec-first mindset - you document what you’re building before you build it  Experience with real-time analytics and sub-second query requirements  Familiarity with data contracts, schema registries, and data mesh principles  Contributions to open-source data projects  Background working in cross-functional product teams    Skills  Relentlessly curious - you dig into new tools and technologies before they have comprehensive documentation  High agency - you don’t wait for permission or detailed instructions; you figure things out and drive forward  Comfortable with ambiguity - you can pick up bleeding-edge LLM tools and make them productive without hand-holding  Self-directed - you identify what needs to be done and do it