Senior Data engineer

Bright Vision Technologies•Bridgewater Township, NJ

5d•Remote

About The Position

Bright Vision Technologies is a forward-thinking software development company dedicated to building innovative solutions that help businesses automate and optimize their operations. We leverage cutting-edge technologies to create scalable, secure, and user-friendly applications. As we continue to grow, we’re looking for a skilled to join our dynamic team and contribute to our mission of transforming business processes through technology. This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential. We are seeking a highly skilled Senior Data Engineer with over 7 years of experience in designing, building, and optimizing data pipelines and architectures. The ideal candidate will have strong expertise in modern data platforms, cloud technologies, and big data frameworks, with a proven ability to deliver scalable solutions that empower analytics and business intelligence.

Requirements

Bachelor’s or Master’s degree in Computer Science, Information Technology, or related field.
7+ years of experience in data engineering, big data, or related roles.
Strong proficiency in: SQL, Python, Scala, or Java
Big Data frameworks: Spark, Hadoop, Kafka
Cloud services: AWS (Glue, Redshift, EMR), Azure (Data Factory, Synapse), GCP (BigQuery, Dataflow)
Data modeling and warehousing: Snowflake, Redshift, Synapse, BigQuery
Experience with workflow orchestration tools (Airflow, Prefect, Dagster).
Solid understanding of data governance, lineage, and security practices.
Hands-on experience with CI/CD pipelines and DevOps practices for data engineering.

Nice To Haves

Exposure to machine learning pipelines and MLOps.
Experience with containerization (Docker, Kubernetes).
Knowledge of real-time data streaming and event-driven architectures.
Relevant certifications (AWS Data Analytics, Azure Data Engineer Associate, GCP

Responsibilities

Design, develop, and maintain scalable ETL/ELT pipelines for structured and unstructured data.
Architect and optimize data warehouses, data lakes, and lakehouse solutions.
Collaborate with data scientists, analysts, and business stakeholders to ensure data availability, quality, and reliability.
Implement data governance, security, and compliance standards across platforms.
Monitor and improve data pipeline performance, scalability, and fault toler
Work with cloud platforms (AWS, Azure, GCP) to deploy and manage data solutions.
Integrate data from diverse sources including APIs, streaming platforms, and enterprise systems.