Job Description

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

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