Data Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Connect outstanding Data Engineers with venture capital-backed startups that are actively seeking data engineering talent.

• Design, construct, and sustain scalable batch and real-time data pipelines.

• Create dependable data models, transformation workflows, and shared datasets for both analytics and operational applications.

• Develop and oversee cloud-based data warehouses, lakehouses, and data platforms.

• Integrate data from product, customer, financial, and third-party systems.

• Set standards for data quality, testing, lineage, observability, and documentation.

• Collaborate with analytics, product, engineering, and business teams to comprehend data requirements.

• Support machine learning and AI initiatives by providing training, feature, and inference data pipelines.

• Enhance the performance, scalability, and cost-effectiveness of data infrastructure.

• Create self-service tools and frameworks to facilitate data discovery and usability.

• Implement access controls, privacy measures, and data governance practices.

• Diagnose pipeline failures, data quality concerns, and performance bottlenecks.

• Assist in defining broader data architecture and technical roadmaps.

• SignalFire reviews applications continuously and may connect candidates with talent partners or leaders from portfolio companies.

⛳️ Requirements

• A minimum of 3 years of experience in data engineering, software engineering, analytics engineering, or a related technical position.

• Proficient programming skills in Python, Java, Scala, or a comparable language.

• Advanced expertise in SQL and experience in designing scalable data models.

• Proven experience in building and maintaining production ETL or ELT pipelines.

• Familiarity with cloud platforms like AWS, GCP, or Azure.

• Experience with modern data warehouses or lakehouse platforms, including Snowflake, BigQuery, Redshift, or Databricks.

• Knowledge of workflow orchestration, transformation, and data quality tools.

• Understanding of distributed systems, data storage formats, and batch or streaming architectures.

• Ability to work collaboratively with both technical and non-technical stakeholders to translate business requirements into data solutions.

• Strong decision-making skills regarding reliability, scalability, governance, and infrastructure trade-offs.

• Experience in venture-backed startups or rapidly growing technology firms is preferred.

• Familiarity with technologies such as Go, Delta Lake, Airflow, Dagster, Prefect, dbt, Fivetran, Airbyte, Kafka, Spark, Flink, Kinesis, Pub/Sub, Docker, Kubernetes, Terraform, Great Expectations, Monte Carlo, Soda, DataHub, OpenLineage, PostgreSQL, MySQL, DynamoDB, MongoDB, and S3.

🏝️ Benefits

• Your profile will be shared with SignalFire portfolio companies, providing visibility into exclusive early-stage opportunities.

• Your profile will be retained for future Data Engineering roles across the portfolio.

• Potential access to opportunities that may not be publicly advertised.