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Senior full-stack developer for a ~5-month project with a Canadian fintech client: migrate applications off an end-of-support Node.js version to a supported one, then provide ongoing support. Stack is Node.js backend, MongoDB, and React; fully remote for LATAM-based candidates working EST hours.
First Senior Data Engineer at Innowave Tech, an AI company serving the semiconductor and advanced manufacturing industry. You'll build the data engineering practice from scratch: on-prem pipelines for process, sensor, image, and annotation data, plus data lakes, governance, and secure infrastructure using Python/Java, Airflow/Dagster, Kafka, and SQL/NoSQL databases. Open only to Singaporeans/PRs.
ABOUT ODAIA ODAIA noun o·da·ia | 'oh-day-yeah An Ancient Greek word referring to "ōdē", the word for song, and the root of melody, harmony, and orchestra. We chose it deliberately: the best commercial…
ODAIA is seeking a Data Implementation Engineer to configure and deploy our AI-driven platform for customers, focusing on data integration and high-quality ETL. You will partner with Customer Success and Engineering…
ABOUT ODAIA ODAIA noun o·da·ia | 'oh-day-yeah An Ancient Greek word referring to \"ōdē\", the word for song, and the root of melody, harmony, and orchestra. We chose it deliberately: the best commercial…
Loop3studio is hiring a remote (Argentina-based) Data Platform Engineer to own ingestion and data warehouse pipelines, building end-to-end data flows and writing dbt models in Python and SQL. Day-to-day work centers on Postgres, Airflow/Dagster orchestration, cloud platforms (AWS/GCP/Azure), and Docker.
Owns the ingestion pipelines, warehouse layer and internal tooling that power VC dealmaking data — reconciling messy company/funding data from sources like PitchBook and Affinity. Day to day: Python, SQL/Postgres, dbt, Airflow/Dagster, Docker and cloud infra (AWS/Azure/GCP), working directly with the analysts and partners who use the data.
Leads technical execution of data infrastructure for government services (tax, criminal justice, safety net): building and optimizing data pipelines, transformations, and cloud data warehousing using SQL, Python/R, dbt, Dagster, Postgres, BigQuery/Snowflake, and Metabase, while mentoring engineers and data scientists. Fully remote within the U.S.
Builds and operates production Python data pipelines and geospatial serving services on AWS that turn raw infrared satellite downlink into calibrated imagery and wildfire/weather products. Focus on pipeline reliability, low latency, observability, and STAC-based geospatial hosting and query APIs. Hybrid role, three days on-site in Denver.
Senior Data Engineer at Inner Circle, an Amsterdam-based screened dating app, owning the entire data platform end to end: building and running pipelines that move product, event, attribution and payment data into Snowflake, and setting the technical direction for the data stack. Core stack: Snowflake, dbt, Dagster, Python, AWS, with AI tooling like Claude Code in daily use.
Data Engineer at the municipality of Almelo designing, building, and maintaining data pipelines that integrate, model, and validate data from multiple sources, including migrating the current MS SQL + FME environment to a modern open-source stack. Key tech: SQL, Python, Git, and orchestrators like Dagster, FME, or Azure Data Factory.
Senior engineer on Chime's Data Platform team designs, builds, and operates the self-serve ETL/ELT infrastructure behind batch and streaming data, owning pipeline reliability, data quality SLAs, and governance (SOX, PII). Core stack: Python or Java/Kotlin, Snowflake/BigQuery/Redshift, Airflow/Dagster/Prefect, Kafka/Flink/Kinesis, dbt, Terraform. Onsite in San Francisco.
Senior engineer on Hive's R&D Data team building the company's cloud-native data platform and ML platform for event marketing — from CDC pipelines and ClickHouse-based storage to feature stores, training/serving infrastructure, and LLM-powered agentic systems. Core stack: Python/Django, ClickHouse, MySQL, MongoDB, ElasticSearch, Redshift, and Airflow or Dagster.
An AVP-level engineer on KKR's Operations Systems team designs, builds, and owns Python backend services and large-scale data pipelines (Spark, ETL/ELT), provisions cloud infrastructure with Terraform, and mentors junior engineers while driving design and code reviews.
A data engineer who owns the pipeline layer for Factory Brain: integrating customer data from ERP, WMS and production/ordering systems, modelling it, and keeping quality high as customer count grows. Core stack is SQL, Python, cloud data warehouses (BigQuery/Snowflake/Redshift) and Airflow/Dagster orchestration, fully remote within Poland.
Fully remote data engineer at INVO (Poland) who owns the data pipeline layer end to end: integrating ERP, WMS and POS sources, modeling data, and maintaining quality, cost and performance of pipelines that feed analytical modules and forecasting models for cross-functional teams.
Coast, a fintech building modern fleet/fuel card payment infrastructure, is hiring a Lead Data Engineer to own its Redshift data warehouse and platform: building Python/Dagster/dbt pipelines, a data catalog, semantic layer, data security (RBAC, tokenization), and AI-ready data access while mentoring teams. NYC-based, 3-4 days in office.
Staff-level, hands-on data engineering role in Belfast (hybrid/remote) owning end-to-end data pipelines and platforms at global scale for a consumer-insights technology business serving major consumer brands. Core stack: Spark, Kafka, dbt, Airflow/Dagster, SQL warehouses and cloud-native infrastructure.
Senior engineer on Wayve's London Data and Orchestration team, building and revamping data pipeline infrastructure and a new DAG-based orchestration system for the autonomous driving data platform — high-volume ingestion, batch inference, and incident response. Core stack: Python, Kafka, Postgres/ClickHouse; Ray/Flyte/Spark a plus.
Backend engineer on Wayve's Data Enrichment Platform team, building and operating services, APIs and data-processing workflows that run large-scale ML inference, evaluation and dataset management over petabytes of driving data on GPU fleets. Core stack: Python, distributed systems, workflow orchestrators and Kubernetes.
