Data Architect

Responsibilities:

• Define and lead architecture, design, and engineering efforts for modernizing legacy data ingestion, ETL, and database systems to cloud-based solutions.
• Design and implement end-to-end data architecture solutions using public cloud platforms, primarily AWS.
• Develop and execute cloud migration strategies, including roadmap planning and implementation of big data solutions.
• Architect, design, and deploy scalable data solutions in cloud and big data environments.
• Create architecture artifacts including HLDs, LLDs, design documents, diagrams, and STTMs.
• Collaborate with stakeholders to gather and analyze business and technical requirements.
• Provide technical leadership and guidance to engineering teams and stakeholders.
• Design and implement data warehousing and modern data lake solutions.
• Develop proof of concepts, prototypes, and reusable frameworks.
• Optimize system performance, scalability, and reliability for large-scale data systems.
• Apply architectural best practices, standards, and methodologies across projects.
• Lead customer migration and transformation initiatives.
• Mentor and coach teams on architecture, design, and best practices.

Qualifications:

• 12+ years of experience in data architecture, engineering, and big data solutions.
• Strong experience with AWS services including Lambda, Glue, EMR, and Redshift.
• Expertise in data warehousing and modern data lake architectures (minimum 5 years).
• Hands-on experience with big data technologies such as Hadoop, Apache Spark, Hive, Kafka, and NoSQL databases (HBase/MongoDB).
• Experience working with large-scale datasets (terabyte to petabyte level).
• Strong knowledge of ETL processes, data ingestion, and cloud-based data solutions.
• Experience with DevOps and Agile methodologies.
• Strong analytical, problem-solving, and communication skills.
• Ability to work independently and in a team-oriented environment.

Preferred Qualifications:

• Proficiency in programming languages such as Python, Scala, or Java.
• Experience with Spark (Python/Scala) and SQL.
• Familiarity with Presto and Snowflake data warehouse.
• Knowledge of Azure cloud platform in addition to AWS.
• Experience in designing and optimizing high-performance data systems.
• Strong interpersonal skills for client interaction and stakeholder management.