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Joseph Sickler

@josephsickler

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Senior Lead Data Engineer with expertise in data platforms and analytics.

United States

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What I'm looking for

I am seeking a role that fosters innovation and collaboration, where I can leverage my data engineering skills to drive impactful business decisions and contribute to a dynamic team.

I am a Senior Lead Data Engineer with over 8 years of hands-on experience in designing, developing, and scaling data platforms at leading technology companies such as Stripe, Amazon, Uber, and Capital One. My specialization lies in building high-throughput ETL/ELT pipelines, event-driven streaming systems, and data lakehouse architectures using tools like Apache Spark, Kafka, Airflow, and AWS. I have a strong command of SQL, Python, and Scala, focusing on distributed data processing and real-time analytics.

Throughout my career, I have routinely improved data infrastructure to enhance system reliability, scalability, and cost-effectiveness. At Stripe, I engineered ETL/ELT pipelines that processed over 8TB of financial data daily with 99.99% reliability and deployed Kafka Streaming systems that significantly reduced data latency. My work has consistently supported critical analytics and driven strategic product decisions, showcasing my ability to deliver impactful solutions in fast-paced environments.

Experience

Work history, roles, and key accomplishments

Current

Senior Lead Data Engineer

Current

Stripe

Aug 2023 - Present (1 year 11 months)

Engineered high-throughput ETL/ELT pipelines using Apache Airflow, Spark, and DeltaLake, processing over 8TB of financial data daily with 99.99% reliability. Deployed Kafka Streaming and AWS Glue-based ingestion systems, reducing end-to-end data latency from 30 minutes to under 5 minutes.

Apache Airflow Spark Kafka Streams AWS Glue Parquet S3 Redshift Athena PostgreSQL

Senior Data Engineer

Amazon

Apr 2021 - Jul 2023 (2 years 3 months)

Built and orchestrated batch and streaming pipelines with Apache Spark, Airflow, and Kafka to process terabyte-scale behavioral data into PostgreSQL and ClickHouse-backed analytics systems. Automated 150+ data quality checks using Great Expectations within Airflow DAGs, reducing pipeline rollback incidents by ~70%.

Apache Spark Airflow Kafka PostgreSQL Clickhouse Great Expectations Presto Apache Superset Redshift RDS SQS Snowflake Pyspark

Data Engineer

Uber

Apr 2018 - Mar 2021 (2 years 11 months)

Built scalable Hive and Spark pipelines processing 20+ billion trip events monthly, feeding into ML training and experimentation systems. Migrated key datasets from Hive to Apache Hudi on S3, achieving 80% reduction in latency for analytics teams.

Hive Spark Hudi S3 Druid Clickhouse Airflow Pandas Avro Kafka Presto

Data Analyst

Capital One

Oct 2016 - Mar 2018 (1 year 5 months)

Analyzed financial transaction trends using SQL, Python (Pandas/Numpy), and Tableau to support credit risk and fraud detection strategies. Created ETL pipelines using Informatica and shell scripting to automate data flow into PostgreSQL and SQL Server environments.

SQL Python Pandas NumPy Tableau Informatica Shell Scripting PostgreSQL SQL Server MySQL MongoDB

Education

Degrees, certifications, and relevant coursework

University of Florida

Master's Degree, Computer Science

Completed a Master's Degree in Computer Science. Focused on advanced topics in computer science, including data structures, algorithms, and software engineering principles.