This role requires candidates who are currently authorized to work in the U.S. without sponsorship, and C2C arrangements are not accepted. This role is remote.

Overview

The Senior Data / AI Engineer is responsible for designing, building, and maintaining enterprise-scale data and analytics solutions using modern cloud-based architectures. This role focuses on developing scalable data integration frameworks, distributed data systems, and analytics pipelines that support advanced reporting, machine learning, and data-driven decision-making across the organization.

This position works closely with data, analytics, and engineering teams to implement best practices in data management, data quality, and security while enabling real-time and batch data processing use cases.

Key Responsibilities

• Design and implement scalable data warehouse and analytics solutions using modern cloud data platforms

• Build and maintain data integration pipelines between transactional systems and analytics environments

• Develop solutions to ingest, transform, and enrich data from internal and external sources

• Support multiple data patterns including real-time streaming, batch processing, BI, advanced analytics, and machine learning

• Develop data products that incorporate enrichment, feature engineering, and ML-ready datasets

• Collaborate with cross-functional teams and contribute to shared technical knowledge and standards

• Apply data management principles to ensure reliability, performance, and data quality

• Follow security best practices related to access control, encryption, and network protection

Required Qualifications

• Bachelor’s degree in Computer Science or a related technical field

• 5+ years of experience building data-driven or analytics solutions

• 3+ years of experience working with cloud platforms (AWS or equivalent)

• Strong experience with Python and SQL for data engineering and analytics

• Hands-on experience with cloud-based data warehouses (e.g., Snowflake, Redshift, Databricks)

• Experience designing and building data pipelines for structured, semi-structured, and unstructured data

• Familiarity with ETL/ELT tools and data integration frameworks

• Strong understanding of data security, governance, and best practices

Preferred Skills

• Experience with real-time or streaming data architectures

• Familiarity with messaging or event-driven platforms (e.g., Kafka or similar)

• Knowledge of cloud-native services for compute, storage, networking, and identity management

• Experience with serverless technologies and infrastructure-as-code concepts

• Exposure to machine learning frameworks and libraries

• Understanding of generative AI concepts such as prompt engineering, retrieval-augmented generation (RAG), or model tuning

• Experience supporting ML model development or deployment pipelines

Additional Requirements

• Strong written and verbal communication skills

• Ability to work independently while managing multiple priorities

• Demonstrated attention to data quality, accuracy, and governance

• Proven ability to meet deadlines and deliver high-quality solutions