Senior Software Engineer - Data

Senior Software Engineer (Data)

What would you be doing

• Watch Reels and YouTube videos every day level up on your fashion sense!
• This is a hands-on engineering role where you will actively build, write production code and not just manage or delegate.
• Architect, build, and optimize data pipelines from event collection to storage and serving, owning the end-to-end data lifecycle with high reliability and performance.
• Lay the foundational groundwork for a self-serve analytics platform where product and business teams can independently derive insights with minimal engineering dependency.
• Build observability systems that proactively surface pipeline failures, data staleness, and anomalies before they impact stakeholders.
• Evaluate and implement AI-native approaches (LLM-assisted quality checks, automated monitoring, natural language access) where they deliver practical improvements.
• Work closely with analytics and product teams to translate complex data requirements into well-scoped engineering execution.
• While your initial focus will be on data infrastructure, there is a clear path to owning broader platform challenges as the team grows.
• Navigate our current stack: Spark, Databricks, Delta Lake (Medallion architecture), BigQuery, Airbyte, and Power BI.

What are we looking for

• If you are a content creator yourself or have worked closely in the social media space, we like you already :)
• 5+ years of software engineering experience, with at least 2+ years deeply involved in scaling data infrastructure. You identify as a strong software engineer first, not just an operator of ETL tools.
• Strong foundation in backend engineering, distributed systems, and cloud platforms (AWS/GCP), paired with a deep understanding of modern data concepts like Lakehouse architectures, data modeling, and batch/streaming processing.
• You care about data quality and reliability as measurable outcomes: pipeline freshness SLAs, schema drift detection, row-count anomalies, and query performance. You've built or operated systems that track these.
• Proven ability to guide peers on engineering best practices, code quality, and scalable system design through code reviews and architecture discussions, without needing formal authority.
• Strong communication skills. You can translate between data engineering and business/analytics stakeholders, making complex tradeoffs understandable to non-technical teams.

Good to Have

• Experience with CDC pipelines and streaming ingestion tools like Debezium, Kafka connectors, or Airbyte.
• Hands-on experience with data partitioning, sharding strategies, and columnar databases like BigQuery for analytical workloads.
• Familiarity with BI tooling and building data models that serve non-technical users directly.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.