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Build and maintain cloud-based data pipelines in Python and SQL, design modern data platforms (Data Lake, Warehouse), and ensure data quality and observability for analytics and AI projects.
Build and maintain the data stack for AI teams that detect objects in satellite imagery using Python, Airflow, PostgreSQL, and AWS, while also contributing to model training pipelines.
Senior Data Engineer modernizes a large bank’s Big Data platforms, migrating batch jobs to Cloudera CDP and Google Cloud using Spark, SQL, and Kubernetes while ensuring performance and reliability.
Build and optimize data pipelines for an aerospace-industry client’s global Data Platform, refactoring Python/Spark jobs to cut costs and adding observability dashboards for FinOps.
Build and maintain robust data pipelines on Google Cloud for analytics and AI clients, using BigQuery, Dataflow, Pub/Sub, and Airflow to process batch and streaming data at scale.
Build and maintain data pipelines and transformations for a SaaS platform serving automotive manufacturers and dealers, using dbt, Python, SQL, AWS S3/Redshift, and Parquet.
Build and maintain data pipelines and transformations for a mobility-focused platform, using AWS S3, dbt, and Redshift to feed analytics and business solutions.
Designs and operates AWS data pipelines in Python, builds Spark workloads, and transforms raw adserver/CRM data into KPIs for media teams.
Build and maintain scalable data pipelines and architectures for enterprise clients, using Python, Spark, Airflow, and cloud storage to enable data-driven decision-making.
Builds and optimizes scalable data pipelines for a Madrid-based bank, using Spark, Scala, Python, Airflow, and cloud migration from Hadoop.
Build and maintain Wizaly’s data pipelines and attribution algorithms using Scala/Spark and SQL, ensuring accurate, real-time marketing performance insights for clients.
Builds and runs cloud-based data pipelines and analytics platforms using GCP/AWS, Spark, Python, and Terraform to support internal decision-making and high-traffic services.
Design and scale backend services, APIs, and data pipelines for AI-powered media workflows, integrating generative models and optimizing performance.
Build and maintain AWS-based data infrastructure, automate pipelines with Terraform, and optimize storage for large-scale datasets using services like OpenSearch and Lake Formation.
Build and scale ML infrastructure for a quantitative trading firm, designing feature stores, MLOps pipelines, and data lakes to support petabyte-scale time-series models in low-latency environments.
Builds and scales Dune’s blockchain data platform, processing petabytes of data with Kotlin/Go to ingest, decode, and optimize SQL queries for on-chain analytics.
Build and optimise cloud-first data pipelines using Azure Data Factory, Synapse, and Databricks to support analytics and AI for UK industries.
Principal Data Engineer designs and builds modern, cloud-native data platforms and real-time pipelines using Databricks, Snowflake, AWS/GCP, Spark, Kafka, and Flink for enterprises and government clients.
Build and maintain large-scale data pipelines and curated datasets for a modern Lakehouse and AI data platform, using Python, SQL, Spark and Snowflake to support analytics and AI use cases at a global bank.
Build and maintain cloud data pipelines on AWS, transform data in Snowflake with dbt and PySpark, and deliver analytics for regulated industries like banking and healthcare.
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