India onlyAt Axelerant, you’ll architect and lead large-scale data engineering initiatives for enterprise customers, leveraging AWS and Snowflake as core platforms. This role places you at the forefront of solving complex data challenges while shaping the long-term technical direction of our clients’ data ecosystems. You’ll work directly with customer leadership, define future-ready architectures, and guide a high-performing engineering team to deliver modern, scalable, cloud-native data solutions.
We are looking for an experienced Staff-level Data Engineer who combines deep hands-on expertise with strong architectural thinking. You will drive technical strategy, ensure robust and secure data platforms, and enable advanced analytics and data-driven decision making. This role also involves mentoring engineers, influencing best practices, and leading the technical execution of large programs.
Your Job Responsibilities
Architecture, Strategy, and Leadership
- Design and own the end-to-end architecture of large-scale data platforms built on platforms like Snowflake and AWS.
- Define data engineering standards, patterns, and best practices for ingestion, modeling, governance, and consumption.
- Lead modernization efforts including data lakehouse design, migration planning, and platform consolidation.
- Partner with customer stakeholders to translate business requirements into scalable technical solutions.
Snowflake and AWS Expertise
- Architect optimized Snowflake environments covering data modeling, workload isolation, clustering, RLS/CLS, data sharing, and performance management.
- Implement secure, cost-efficient, cloud-native pipelines using AWS services such as S3, Athena, Redshift, Glue, Lambda, Kinesis, IAM, Step Functions, and CloudWatch.
- Leverage Snowflake capabilities including Snowpark, Streams and Tasks, Materialized Views, Data Marketplace, and Time Travel.
Pipeline Design and Optimization
- Oversee the development of high-volume batch and streaming pipelines using Spark, Kafka, Airflow, or similar technologies.
- Implement robust ETL and ELT frameworks ensuring data accuracy, lineage, observability, and governance.
- Analyze and optimize data workflows for performance, scalability, and cost efficiency.
Customer Collaboration and Technical Advisory
- Serve as the primary technical partner for customer teams, communicating architectural decisions and trade-offs.
- Lead technical workshops, discovery sessions, and solution reviews with both technical and non-technical stakeholders.
- Ensure alignment between customer goals and Axelerant’s delivery approach while influencing long-term data strategy.
Team Leadership and Mentorship
- Guide and mentor a team of data engineers, fostering a collaborative, growth-oriented environment.
- Provide technical oversight across workstreams, ensuring quality, consistency, and engineering excellence.
- Facilitate knowledge sharing, code reviews, design sessions, and continuous improvement practices.
Governance, Security, and Compliance
- Establish data governance frameworks including cataloging, lineage, access controls, quality checks, and lifecycle management.
- Ensure compliance with enterprise security standards and regulatory policies across AWS and Snowflake workflows.
- Promote DataOps principles including automation, CI/CD for pipelines, testing strategies, and monitoring.
Innovation and Continuous Improvement
- Stay current with emerging tools, technologies, and patterns in data engineering and cloud architecture.
- Recommend and introduce innovative solutions to enhance customer outcomes and internal accelerators.
- Contribute to building reusable components, architectural templates, and best practice guides.
Skills, Knowledge & Expertise
- Eight or more years of experience designing and delivering large-scale data solutions.
- Deep expertise with Snowflake architecture including modeling, security, orchestration, and optimization.
- Strong experience architecting data platforms on AWS with hands-on knowledge of core data services.
- Proficiency in Python, Scala, or Java with experience building scalable data pipelines.
- Strong understanding of distributed processing frameworks like Spark or Flink and streaming tools like Kafka or Kinesis.
- Solid grounding in data modeling, warehouse and lakehouse design patterns, and query optimization.
- Experience with orchestration tools such as Apache Airflow or Prefect.
- Comfortable with containerization and orchestration using Docker and Kubernetes.
- Strong understanding of data governance, privacy, and security best practices.
- Excellent communication skills to work effectively with customers, engineering teams, and leadership.
- Proven leadership experience mentoring teams and driving large technical initiatives.
Why Work At Axelerant?
- Be part of an AI-first, remote-first digital agency that’s shaping the future of customer experiences.
- Collaborate with global teams and leading platform partners to solve meaningful challenges.
- Enjoy a culture that supports autonomy, continuous learning, and work-life harmony.
