Data Lake / Lakehouse Engineer Profiles

Architecting petabyte-scale data infrastructure. Built scalable data ingestion pipelines with Apache Iceberg, Kafka, Spark (Scala/Python), Kubernetes (EKS), Terraform/CDK, Snowflake, and Bedrock/ML Infrastructure. Strong EKS/Iceberg/Spark combination at scale.

Technical Data leader for AWS Data Center org who built distributed, scalable data lake systems from the ground up. Architected and operationalized exabyte-scale infrastructure using Apache Iceberg, Trino, Glue, and Lake Formation. Strong lakehouse and data platform credentials.

The Insights team used Flink and Spark for moving data around and Apache Iceberg for the OLAP data lake. Also supported OLTP workloads via Postgres across kubernetes-based platforms. Combines real-time streaming with lakehouse storage.

Built a near-real-time data lake using Spark and big data processing at scale. Leveraged AWS Bedrock for automated data quality detection. Strong ETL platform background with DDMS (data catalog, lineage tracking, freshness monitoring). US patent-approved ETL platform.

Apache Spark Expert and Apache Iceberg specialist. Engineered a Lakehouse architecture to process large-scale data daily with high reliability. Dual cloud certified (AWS + Azure). Manages Iceberg format for seamless tracking and analysis of customer data at Amazon scale.

Staff Data Engineer at Meta with expertise in Kubernetes, Buildkite, Cloud Deployment, and Infrastructure Automation. GCP Certified. Architecting AI and cloud data infrastructure at Meta scale.

Senior software engineer with extensive experience at Meta. Orchestrated workloads in Kubernetes environments with domain-driven and behavioral-driven design. Strong data engineering foundations supporting Meta's data infrastructure.

Staff Data Engineer at Airbnb with $600k total compensation. Entity extraction and NLP with Apache Spark. One of the most followed data engineers on LinkedIn (518k followers) and founder of DataExpert.io. Strong Spark and distributed systems background.

Lakehouse | Snowflake | Databricks | Apache Iceberg | Data Vault 2.0. Multi-cloud expertise across AWS, GCP, and Azure. Strong in Spark, Python, SQL. Certified CCA175 (Spark). Data engineering with broad lakehouse and Data Vault architecture.

Lead Data Engineer certified in both AWS and Azure. CCA Spark and Hadoop Developer (CCA175). Strong PySpark and big data processing background across dual-cloud environments.

Senior Data Engineer with 6+ years of experience. GCP and AWS certified. Apache Spark (PySpark), Kafka, Scala, Airflow specialist. Strong data modeling and multi-cloud platform experience at NBCUniversal.

Data Engineer with hands-on experience in Apache Spark, Apache Iceberg, Lakehouse Architecture, Azure, and AWS. Directly matches the lakehouse + Iceberg + Spark + cloud profile criteria.

Senior Data Engineer with AWS & Snowflake and Apache Iceberg Lakehouse expertise. Spark (EMR), Airflow, dbt. Modern data platforms specialist combining Iceberg lakehouse with AWS.

Big Data / ETL Engineer at AWS. Expertise in Spark, SQL, Python, Kafka, Databricks, Snowflake, and Apache Iceberg with Unity Catalog. Led initiatives on Databricks with Iceberg integration for lakehouse governance.

Data Engineer 2 with strong technical stack: Apache Spark, PySpark, Apache Airflow, AWS EMR, Amazon Redshift, Delta Lake, Apache Iceberg, Data Modeling, Data Quality, ETL/ELT. Good all-around data platform profile.

Designed lakehouse architectures with Delta Lake and Apache Iceberg while implementing governance through Unity Catalog and AWS Glue Data Catalog. Strong Spark and AWS Glue background. Good combination of lakehouse architecture and governance.

Databricks Certified Data Engineer Associate. Hands-on with Apache Iceberg, Kubernetes, Databricks, Linux. Agile Practitioner with strong Spark and distributed systems fundamentals.

Senior Data Engineer working across AWS, Azure, and GCP. Apache Iceberg and Kubernetes expertise with Microsoft Azure Data Engineer Associate certification. Strong multi-cloud data engineering background.

Senior engineering leader who built the Lakehouse — the data foundation supporting $1B+ in product. Built scalable data ingestion with Apache Spark, Kafka, Azure Data Lake, and Apache Iceberg. Strong enterprise-scale data platform credentials.

Principal Data Engineer with expertise across AWS, GCP, Snowflake, Databricks, and Apache Spark. Designed a distributed AWS data lake improving ingestion and processing by 60%. Strong AI platform and lake architecture background.