Senior Data Architect Engineering Lead

We are seeking a highly skilled and experienced professional (Senior Data Architect & Engineering Lead) to work remotely from anywhere in the US on our W2 leading the design implementation and management of endtoend enterprisegrade data solutions for our Huntsville Texas client. This role involves expertise in building and optimizing data warehouses data lakes and Lakehouse platforms with a strong emphasis on data engineering data science and machine learning. You will work closely with crossfunctional teams to create scalable and robust architecture that supports advanced analytics and machine learning use cases while adhering to industry standards and best practices.

Responsibilities Include:

* Architect design and manage the entire data lifecycle from data ingestion transformation storage and processing to advanced analytics and machine learning databases and largescale processing systems.

* Implement robust data governance frameworks including metadata management lineage tracking security compliance and business glossary development.

* Identify design and implement internal process improvements including redesigning infrastructure for greater scalability optimizing data delivery and automating manual processes.

* Ensure high data quality and reliability through automated data validation and testing and provide high quality clean and usable data from data sets of varying states of disorder.

* Develop and enforce architecture standards patterns and reference models for largescale data platforms.

* Architect and implement Lambda and Kappa architectures for realtime and batch data processing workflows along with strong data modeling capabilities.

* Ability to identify and implement the most appropriate data management system and enable integration capabilities for external tools to perform ingestion compilation analytics and visualization.

Job Qualifications

1. Ability to define and manage data flows and data pipelines with related scripting knowledge for importing.

2. Strong data modeling capabilities.

3. Ability to identify and implement the most appropriate data management system.

4. Provide high quality clean and usable data from data sets of varying states of disorder.

5. Data/Query validation proficiency; and

6. Demonstrate a wide range of technical competencies including tools such as SAP Oracle Cassandra MySQL Redis PostgreSQL MongoDB and Hive.

Requirements

* Proficient in SQL Python and big data processing frameworks (e.g. Spark Flink).

* Strong experience with cloud platforms (AWS Azure GCP) and related data services.

* Handson experience with data warehousing tools (e.g. Snowflake Redshift BigQuery) Databricks running on multiple cloud platforms (AWS Azure and GCP) and data lake technologies (e.g. S3 ADLS HDFS).

* Expertise in containerization and orchestration tools like Docker and Kubernetes.

* Knowledge of MLOps frameworks and tools (e.g. MLflow Kubeflow Airflow).

* Experience with realtime streaming architectures (e.g. Kafka Kinesis).

* Familiarity with Lambda and Kappa architectures for data processing.

* Enable integration capabilities for external tools to perform ingestion compilation analytics and visualization.

Preferred

* Certifications in cloud platforms or datarelated technologies.

* Familiarity with graph databases NoSQL or timeseries databases.

* Knowledge of data privacy regulations (e.g. GDPR CCPA) and compliance requirements.

* Experience in implementing and managing business glossaries data governance rules metadata lineage and ensuring data quality.

* Highly experienced with AWS cloud platform and Databricks Lakehouse.

* Education: Bachelors or Masters degree in Computer Science Data Science Engineering or a related field.