Juan S.

Sr Data Engineer @ Lumenalta

About

Senior Data Engineer / Data Architect with +8 years of experience designing and optimizing large-scale data pipelines across industries including healthcare, finance, insurance, and retail. I specialize in building robust data architectures using: Snowflake, Databricks, Spark, Azure Data Factory, AWS, and Kafka End-to-end ETL pipelines, real-time data streaming, and batch processing Data migration from legacy systems like Teradata, SQL Server, Informatica and On-Prem to Cloud. My recent work includes leading projects for clients such as CIGNA, Stanley Black & Decker, West Bend Insurance, and CitiBanamex, where I delivered: Scalable cloud data solutions Performance tuning for big data environments Secure data transformation layers with encryption, masking, and audit controls 🔍 I’m passionate about building modern data platforms that enable smart business decisions. 🌎 Based in Mexico, I’m fully remote and available to collaborate with international teams. I work fluently in both English and Spanish, and I’m familiar with operating in Agile environments with cross-functional teams. 📬 I currently work as an independent contractor, partnering with clients across Mexico, the U.S., and globally. I’m open to B2B collaborations on a full-time or project basis and bring a proactive, reliable approach to every engagement.

Country

Mexico

City

Mexico City

Industry

Information Technology & Services

Skill

DynamoDB, Github Actions, High Performance Computing (HPC), Multi-objective Optimization, Distributed Systems, Algorithm Design & Analysis, Numerical Methods, Apache Spark Streaming, Apache Kafka, Jenkins, Cloudera, Hadoop, AWS Lambda, AWS EMR, Data Build Tool (DBT), Talend, Markdown, Databricks, Amazon Web Services (AWS), Continuous Integration and Continuous Delivery (CI/CD)

Experience

Sr Data Engineer

Lumenalta

2025-5 - Present · 1 yr 5 mos

New York, United States

🛠️ Tech Stack: AWS (Lambda, SQS, IAM, DynamoDB, Athena), Apache Airflow, Apache Iceberg, Python (CLI, ETL), PySpark, SQL (MySQL, SQL Server, Oracle, PostgreSQL), GitHub Actions, CircleCI

Sr Data Engineer

Inetum

2024-11 - 2025-4 · 6 mos

Mexico City, Mexico

INETUM (Mexico) | Client: Slalom (USA) / West Bend Insurance, (USA) 🛠️ Tech Stack: Snowflake, Azure Data Factory, SQL Server, Informatica PowerCenter, Control-M, Shell Scripting, Azure DevOps, Python, Spark

Sr Data Engineer

CGI

2023-5 - 2024-8 · 1 yr 4 mos

Lafayette, Louisiana, United States

CGI Technologies (USA) | Client: CIGNA (USA) 🛠️ Tech Stack: Databricks, AWS, PySpark, YARN, AWS S3, SQL, Linux, Shell Scripting, GitHub

Data Platform Engineer / Sr Data Engineer

HCLTech

2020-3 - 2023-3 · 3 yrs 1 mo

Hartford, Connecticut, United States

HCL Technologies (USA) | Client: Stanley Black & Decker (USA) 🛠️ Tech Stack: Snowflake, PySpark, Hadoop, AWS Lambda, AWS EMR, DBT, Talend, SQL, Linux, Bitbucket, Jenkins, Airflow, Collibra, Caspian

Big Data Architect

Banamex

2018-9 - 2020-3 · 1 yr 7 mos

México, Ciudad de México, México

Everis (Mexico) | Client: CitiBanamex 🛠️ Tech Stack: PySpark, Scala, Python, Sqoop, Teradata, Oracle, HDFS, HBase, Hive, Impala, Kudu, Cloudera, Bitbucket, Jenkins, Spring Boot, REST APIs, Agile/Scrum

Big Data Developer

Nielsen IBOPE

2018-6 - 2018-9 · 4 mos

México, Ciudad de México, México

EON (Mexico) | Client: Nielsen IBOPE 🛠️ Tech Stack: Spark, Spark Streaming, Kafka, Java, Hadoop, Hive, HBase, Pig, Impala, Sqoop, Cloudera, TIBCO, Bitbucket, Jenkins, Artifactory, JSON, XML

Big Data Developer

Grupo Salinas

2017-1 - 2018-6 · 1 yr 6 mos

México, Ciudad de México, México

Grupo Salinas (Mexico) | Client: Banco Azteca 🛠️ Tech Stack: Spark, Scala, Python, Spark Streaming, Hadoop, HDFS, Hive, HBase, Kudu, TIBCO, Flume, Pig, Sqoop, Impala, Cloudera, GIT, XML, JSON, SQL

Education

Centro de Investigación y de Estudios Avanzados del IPN

Computer Science

2014-9 - 2016-12 · 2 yrs 4 mos

Master’s focused on multi-objective optimization, evolutionary algorithms, and high-performance computing. Gained expertise in metaheuristics like Genetic Algorithms and PSO for solving complex optimization problems, applicable to data engineering tasks such as resource allocation and pipeline tuning. Developed parallel and distributed programs using MPI, OpenMP, CUDA, and Pthreads, enhancing performance for large-scale data workloads. Strong foundation in numerical analysis and algorithm design, with hands-on programming in C++, Python, and Matlab. This background now supports advanced data processing, query optimization, and system performance tuning in cloud and big data platforms like Spark, Snowflake, Databricks, and Azure.