Senior Data Engineer (Remote, Contractual) [TH003]

Smart Working Solutions

DelhiRemoteContract

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About Smart Working At Smart Working, we believe your job should not only look right on paper but also feel right every day. This isn't just another remote opportunity—it's about finding where you truly belong, no matter where you are. From day one, you're welcomed into a genuine community that values your growth and well-being. Our mission is simple: to break down geographic barriers and connect skilled professionals with outstanding global teams and products for full-time, long-term roles. We help you discover meaningful work with teams that invest in your success, where you're empowered to grow personally and professionally. Join one of the highest-rated workplaces on Glassdoor and experience what it means to thrive in a truly remote-first world. About the Role We are seeking a highly experienced Senior Data Engineer on a contract basis to join an expanding data team supporting multiple leading iGaming and casino brands, with a particular focus on Metawin and HIT, both of which have a strong crypto focus. This role offers the opportunity to make a direct impact on the organisation’s data platform and roadmap delivery. You will play a critical role in optimising and modernising the data ecosystem, improving performance across Snowflake, developing scalable ingestion and transformation pipelines, and helping drive the transition towards real-time data processing. You will work closely with data science teams, product teams, operations, and other stakeholders in a fast-paced environment where collaboration, clear communication, and documentation are highly valued. The organisation embraces AI-first ways of working, and you will be expected to leverage tools such as Claude, GitHub Copilot, Gemini, and other AI assistants to improve productivity, automate repetitive tasks, and accelerate development. This is an excellent opportunity for a Senior Data Engineer with deep AWS, Snowflake, and dbt expertise who is ready to hit the ground running and contribute immediately within a modern data platform environment. Responsibilities Manage and optimise Snowflake data warehouses. Overhaul Snowflake warehouse performance through materialisation strategies, dynamic tables, and clustering optimisation. Build scalable ETL/ELT pipelines using dbt, Airflow, Fivetran, and AWS DMS. Build ingestion pipelines using DMS and Fivetran. Develop modelling layers in dbt using medallion architecture principles. Transform raw data into clean, reliable, and business-ready models using dbt and AI-assisted tooling for documentation and testing. Integrate data from multiple sources, including CRM systems, payment platforms, gaming platforms, and other operational systems. Own initiatives focused on data quality improvements and monitoring, including anomaly detection and automated alerting. Monitor and optimise platform performance, cost efficiency, and security. Work closely with cross-functional teams across product development, data, operations, and analytics functions. Collaborate with the data science team and support colleagues with reporting and analytics activities when required. Support the organisation’s move towards real-time data ingestion and ETL using technologies such as DMS, Kafka, and Kinesis. Help mentor other engineers within the team. Contribute to the team's AI strategy and promote effective use of AI tools across engineering workflows. Produce and maintain clear, comprehensive documentation to support scalability, transparency, and long-term platform sustainability. Communicate effectively with both technical and non-technical stakeholders and proactively raise blockers when encountered. Requirements 7+ years in Data Engineering. Solid hands-on experience with AWS. You really know ELT design and data warehousing best practices. You're an expert in optimising Snowflake. You're a dbt pro (macros, testing, modularisation). Excellent SQL and Python skills. Good CI/CD and Git skills. You have used AI coding assistants to work efficiently. Nice To Haves Experience building pipeline to handle high-volume data. Know the iGaming lingo (GGR, LTV, RTP, acquisition KPIs). Experience with affiliate or game provider data feeds. Familiarity with real-time data ingestion. Exposure to data science/ML pipelines (SageMaker, Bedrock). Used AI tools for monitoring or query optimisation before. QuickSight experience (especially SPICE/Direct Query). Benefits Fixed Shifts: 12:00 PM - 9:30 PM IST (Summer) | 1:00 PM - 10:30 PM IST (Winter) No Weekend Work: Real work-life balance, not just words Support That Matters: Mentorship, community, and forums where ideas are shared True Belonging: A long-term career where your contributions are valued

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