Data Engineer Senior

Andy Anwin

Senior Data Engineer

+1-860-***-**** ************@*****.*** Hartford, CT, USA

Summary

Results-oriented Data Engineer with over 14 years of experience in designing,

implementing, and optimizing scalable data infrastructures and ETL processes. Proven

track record in enhancing data flow efficiency and enabling real-time analytics across

distributed systems. Expertise in leveraging cloud data platforms and big data technologies,

including Apache Spark, Kafka, and Snowflake, to drive strategic data initiatives. Adept at

collaborating with cross-functional teams to deliver high-quality data solutions that meet

business objectives. Strong background in data governance, data quality assurance, and

performance tuning, ensuring reliable and accessible data for analytics. Committed to

continuous improvement and innovation in data engineering practices to support

organizational growth and decision-making.

Skills

Cloud & Infrastructure:

AWS (EC2, S3, Lambda, IAM, EMR, Redshift), Azure, GCP (BigQuery,

Dataflow), Cloudera, Kubernetes, Docker, Terraform (IaC)

Data Pipelines & Orchestration:

Apache Airflow, Azure Data Factory, Google Dataflow, Apache Beam,

ETL/ELT, dbt, REST APIs

Big Data & Distributed Processing:

Apache Spark (PySpark, Scala), Apache Kafka, Hadoop, Hive, EMR, Data Lakes,

Petabyte-scale data handling

Programming & Scripting:

Python, Scala, Java, SQL, HiveQL, Bash, Jupyter, NumPy, Pandas

Streaming & Real-time Systems:

Kafka, Spark Streaming, Event-driven architectures, Real-time ingestion and

processing

DevOps & CI/CD:

Git, GitHub, JIRA, Docker, Kubernetes, Terraform, CI/CD pipelines

Monitoring & Visualization:

Grafana, Prometheus, Custom dashboards, System & pipeline metrics

Security & Compliance:

HIPAA-compliant data handling, Access control (IAM), Secure data pipelines

Analytics & Modeling:

Google BigQuery, dbt, Redshift, Data modeling, Query optimization

Project Methodologies:

Agile, Scrum, Kanban

Experience

Senior Data Engineer

DataNova Solutions – Austin, TX

May 2024 – Present

Designed scalable data pipelines using Apache Airflow, dbt, and Snowflake for

client-facing analytics applications

Migrated legacy batch ETL systems to real-time processing using Kafka and

AWS Kinesis

Built reusable data quality monitoring components using Great Expectations and

custom Python scripts

Collaborated with analytics teams to optimize data models in Redshift and

improve query performance

Deployed containerized data services via Docker and orchestrated deployment

with GitLab CI/CD

Lead Data Engineer

ClearMetrics Inc. – Denver, CO

June 2020– April 2024

Developed and maintained ETL workflows using Python, SQL, and Amazon

Redshift

Built parameterized data pipelines in Apache Airflow for ingestion and

transformation tasks

Implemented star and snowflake schemas to support marketing and customer

intelligence analytics

Created data marts and curated datasets for BI teams using dbt and Looker

Automated data loads from REST APIs, S3 buckets, and on-prem databases

Monitored pipeline performance and managed failure recovery using AWS

CloudWatch

Data Engineer

Google – Mountain View, CA

March 2019 – May 2020

Led end-to-end development of high-throughput data ingestion pipelines using

Dataflow and BigQuery

Partnered with product teams to create scalable event tracking strategies for Ads

performance analytics

Integrated machine learning workflows with Vertex AI and orchestrated model

training pipelines

Designed and implemented secure data governance policies in compliance with

global privacy standards

Automated complex data workflows using Cloud Functions and Terraform for

GCP infrastructure

Delivered unified data views by building robust data marts for cross-functional

reporting

Big Data Engineer

ClearMetrics Inc. – Denver, CO

June 2015 – February 2019

Built ELT pipelines for customer usage data using Python, SQL, and Amazon

Redshift

Implemented SCD Type 2 data models to support historical reporting needs in

marketing dashboards

Developed and maintained Airflow DAGs for orchestration of multi-stage data

workflows

Collaborated with data scientists to engineer features for predictive churn models

Introduced version control and modular design patterns across data transformation

scripts

Integrated REST API data sources and scheduled ingestion jobs using Lambda

and CloudWatch

Junior Data Engineer

TechAxis Analytics – Chicago, IL

July 2011 – May 2015

Assisted in data warehouse development using SQL Server and SSIS for business

intelligence reporting

Supported daily ETL operations and performed root cause analysis on data load

failures

Designed initial schema models for transactional and aggregated data layers

Built stored procedures and automated data validations to ensure data accuracy

Participated in migration from on-prem SQL to AWS-based infrastructure using

EC2 and S3

Education

Bachelor of Science in Computer Science

University of Engineering and Technology

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