Data Engineer Solution Architect
ADAJob description
About ADA
ADA is the Data and AI Experience Company. Present in 14 markets globally, we build intelligent experiences that power enterprise growth, spanning identity and authentication, personalization, commerce, and data & AI foundations; where every touchpoint earns trust, every interaction creates value, and every decision runs on real-time intelligence, so enterprises can stay ahead and deliver measurable outcomes. Our mission is to build the world's most intelligent growth platform for every client we serve.
We work with over 1,500 global brands across CPG, Retail, Telco, BFSI, and Healthcare.
Job Title: Data Engineer Solution Architect Experience: 10–15 Years
Role Overview
We are seeking an experienced Data Architect to design and lead the implementation of modern data platforms and analytics ecosystems. The ideal candidate will have strong expertise in Databricks, Snowflake, cloud-native data architectures across AWS, Azure GCP, as well as real-time streaming ecosystems.
This role requires both deep technical architecture capabilities and client-facing skills, as the candidate will work closely with internal engineering teams and external clients to define scalable data solutions.
The Data
Architect will also support pre-sales initiatives, helping shape solution architectures, participate in discovery workshops, and contribute to proposals and technical strategy discussions.
Key Responsibilities
- Design and implement modern data architectures, including lakehouse and cloud data warehouse solutions using Databricks and Snowflake.
- Define end-to-end data platform architecture covering data ingestion, processing, storage, governance, and analytics layers.
- Architect and optimize data platforms across AWS, Azure, and GCP cloud environments.
- Lead the development of scalable ETL/ELT pipelines using technologies such as Spark, Python, SQL, and orchestration tools.
- Establish standards for data modeling, data quality, security, and governance frameworks.
- Engage with clients during pre-sales and solution discovery, providing architecture guidance and participating in technical workshops.
- Collaborate with sales teams to create solution proposals, architecture diagrams, and effort estimates for client opportunities.
- Provide technical leadership and architecture governance to engineering teams throughout the project lifecycle.
- 10 years of experience in data engineering, analytics platforms, or enterprise data architecture.
- Strong expertise in Databricks (Spark, Delta Lake) and Snowflake data platform architecture.
- Hands-on experience across AWS, Azure, and GCP cloud ecosystems for building scalable data platforms.
- Proficiency in data pipeline development using Python, Spark, SQL, and orchestration tools such as Airflow or similar.
- Strong knowledge of data modeling techniques (dimensional modeling, normalized models, data vault).
- Experience designing real-time and batch data processing architectures, including streaming and CDC pipelines.
- Ability to conduct client workshops, architecture discussions, and technical presentations during pre-sales engagements.
- Excellent communication and stakeholder management skills, with the ability to translate business needs into technical solutions.
- Experience building data accelerators or reusable platform frameworks.
- Exposure to AI/ML data pipelines and MLOps architectures.
- Certifications in Databricks, Snowflake, AWS, Azure, or GCP at Professional category.
Pioneers in data and analytics, we are powering global marketing and commerce digital transformation with data and AI-led impact. Learn more here!
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