Hire Data Engineers Who Build Reliable Data Pipelines

Tech stack: Python, SQL, Apache Airflow, Snowflake, AWS, Elasticsearch, Redis, Apache Hive, Docker, Kubernetes

A data engineer with 4 years of commercial experience in cloud data infrastructure and pipeline automation. Builds data lake architectures on AWS, with Apache Airflow orchestrating ingestion and transformation jobs. Implements warehouse models in Snowflake and caching layers with Redis and Elasticsearch. Has experience automating pipelines across containerized environments with Docker and Kubernetes.

Tech stack: Python, SQL, Apache Spark, Apache Kafka, Azure Data Factory, Databricks, PostgreSQL, MongoDB, Docker

A data engineer with 5 years of experience building production ETL pipelines and data warehouses. Builds batch and streaming pipelines in Apache Spark, with Apache Kafka moving events between systems. Implements warehouse and analytics layers in Databricks and Azure Data Factory. Has experience modeling data across PostgreSQL and MongoDB for analytics workloads.

Tech stack: Python, Scala, SQL, Apache Spark, Flink, Kafka, AWS, Google BigQuery, Airflow, Docker, Elasticsearch, Git

A skilled data engineer with 5 years of experience in distributed data processing and real-time analytics. Deep knowledge of the Apache Spark ecosystem and streaming technologies. Built data pipelines that handle terabyte-scale datasets with optimized performance.

Experienced in implementing data quality checks and monitoring systems. Strong background in both cloud and on-premise data infrastructure.

Tech stack: Python, SQL, Apache Spark, Apache Kafka, Azure SQL, Power BI, Apache Airflow, Docker, Flask

Experienced integration specialist with 3 years of commercial experience building analytics platforms from ingestion through reporting. Builds ETL pipelines in Apache Spark and Apache Airflow, with Azure SQL as the warehouse layer. Implements reporting datasets that feed Power BI dashboards. Has experience exposing data services through Flask APIs for product teams.

Tech stack: Scala, Java, Python, Apache Spark, Apache Flink, Databricks, Google BigQuery, Apache Pulsar, Kubernetes, Terraform

Senior data engineer with 6 years of experience specializing in real-time data processing. Proficient in building streaming pipelines using Flink and Pulsar for high-throughput data ingestion. Implemented machine learning data pipelines and automated deployment processes with Kubernetes. Proven track record of mentoring junior engineers and establishing data engineering best practices.

Tech stack: Python, Scala, SQL, Apache Spark, Amazon Redshift, Apache Kafka, Redis, Docker, Jenkins, TensorFlow

ML-focused engineer with 4 years of experience building intelligent data processing systems. Builds pipelines in Apache Spark and Apache Kafka, with Amazon Redshift as the analytics warehouse. Implements feature pipelines that feed TensorFlow models, with Redis for low-latency lookups. Has experience automating deployments with Jenkins and Docker across Scala and Python services.

Tech stack: Python, Java, SQL, Apache Hadoop, Apache Hive, Cassandra, Elasticsearch, Azure DevOps, Kubernetes, Git

Senior data engineer with 7 years of commercial experience in big data processing and NoSQL database management. Builds large-scale batch pipelines in Apache Hadoop and Hive, with Cassandra handling distributed storage. Implements search and analytics layers in Elasticsearch.