Senior/Principal Data Engineer

• Design, build, and maintain scalable, secure, and reliable data platforms, pipelines, and data products

• Drive architecture discussions related to data modeling, storage strategies, integration patterns, and platform evolution

• Take end-to-end ownership of technical solutions and contribute to architectural and engineering decision-making

• Develop and implement batch and streaming data solutions using modern cloud-native technologies

• Lead platform modernization initiatives and continuous technical improvements

• Establish and promote engineering best practices including CI/CD, testing, observability, security, and data quality

• Mentor and support Data Engineers through technical guidance, code reviews, and knowledge sharing

• Lead onboarding activities for new team members and support their integration into the engineering organization

• Collaborate with Product Managers, Software Engineers, Analysts, and business stakeholders to deliver scalable data solutions

• Contribute to technical roadmaps and influence engineering direction across teams

• 5–8+ years of experience in Software Engineering, including 3–5+ years of hands-on Data Engineering experience

• Upper-Intermediate or higher English level

• Strong experience building and operating scalable data platforms and pipelines in cloud environments

• Advanced SQL knowledge and strong understanding of data modeling and data architecture principles

• Strong programming skills in Python

• Hands-on experience with Apache Spark, Databricks, and Kafka

• Experience developing ETL/ELT pipelines and orchestration workflows

• Strong AWS cloud experience and knowledge of cloud-native data services

• Experience designing modern data warehouse or lakehouse architectures

• Strong system design and problem-solving skills

• Ability to balance business and technical priorities while making architecture decisions

• Experience mentoring engineers and driving engineering best practices

• Strong communication and collaboration skills across technical and business teams

WILL BE A PLUS

• Experience with Scala or Java

• Experience with real-time data streaming architectures

• Exposure to large-scale distributed systems

• Experience with observability and data quality frameworks

• Experience contributing to platform modernization programs

• Background in enterprise analytics or machine learning data platforms

PERSONAL PROFILE

• Strong ownership mindset

• Leadership-oriented and proactive

• Excellent collaboration and stakeholder management skills

• Strategic and architecture-driven thinking

• Passion for mentoring and team development

• Ability to work in fast-paced and evolving technical environments

Are you passionate about building large-scale data platforms that power analytics, machine learning, and strategic business decisions? We are looking for a Senior/Principal Data Engineer to join a distributed engineering team focused on modern cloud-native data solutions.

This is a fully remote opportunity for experienced Data Engineers who enjoy solving complex technical challenges, driving architecture decisions, and mentoring engineering teams. You will work with modern technologies across batch and real-time data processing environments while influencing the technical direction of enterprise-scale platforms.

We at Sigma Software create meaningful solutions together with talented professionals worldwide. Joining our team means working on impactful products, collaborating with strong engineering communities, and having opportunities for continuous professional growth and technical leadership.

CUSTOMER

Our customer's project focuses on enterprise-grade data platforms supporting analytics, reporting, machine learning, and large-scale business operations. The environment includes distributed cloud infrastructure, modern engineering practices, and high-performance data processing solutions designed for scalability, reliability, and operational excellence.

PROJECT

You will join a team responsible for designing and scaling modern data infrastructure capable of handling both batch and streaming workloads. The project includes platform modernization initiatives, architecture evolution, and implementation of secure and reliable data pipelines using cloud-native technologies. The role combines hands-on engineering, architectural ownership, and cross-functional collaboration with Product Managers, Analysts, and Software Engineers.

Key Technologies: AWS, Python, Apache Spark, Databricks, Kafka, SQL, ETL/ELT, Streaming Data Processing

Originally posted on Himalayas