Technical Architect

Job Description

Data Architecture and Design:-
•    Design and implement scalable, high-performance data architecture solutions to support analytics, reporting, and data science requirements.
•    Create and maintain data models, schemas, and blueprints for cloud platforms.
•    Define and enforce data governance, quality, and security standards across all platforms.
Cloud and Data Engineering
•    Develop and maintain ETL/ELT pipelines for extracting, transforming, and loading data using tools like Databricks, AWS Glue, and AWS Lambda.
•    Leverage AWS services such as S3, Redshift, Athena, Dynamo DB, and EMR for data storage and processing.
•    Optimize the performance of data pipelines and ensure the availability of data systems. 
Analytics and Reporting
•    Collaborate with analytics and business intelligence teams to integrate data sources and enable advanced reporting.
•    Implement and manage reporting transforming from existing Qlik to Sigma Enterprise BI to provide intuitive dashboards and insights.
•    Partner with stakeholders to understand business requirements and translate them into data and analytics solutions.
 Collaboration and Leadership
•    Work closely with cross-functional teams, including Data Scientists, Analysts, and Developers, to ensure seamless data flow and accessibility.
•    Mentor junior team members in best practices for data architecture and engineering.
•    Stay up-to-date with emerging technologies and advocate for the adoption of innovative solutions.
Skills & Qualification
•    12+ Years of relevant experience
•    Bachelors or Master’s degree in Computer Science, Data Science, or a related field.
•    AWS certifications (e.g., AWS Certified Data Analytics – Specialty, AWS Certified Solutions Architect).
•    Prior experience in implementing real-time data pipelines and streaming solutions.
•    Familiarity with machine learning workflows and tools.
Primary Skill(s): Data Architect
Technical Skills
•    Proficiency with AWS Cloud Services (e.g., S3, Redshift, Glue, Lambda, Athena, DynamoDB).
•    Hands-on experience with Databricks for data engineering and analytics workloads.
•    Expertise in designing and building data pipelines and workflows using tools like Apache Spark and Databricks.
•    Strong understanding of relational databases, data lakes, and data warehousing concepts.
•    Experience with Qlik, Sigma or other reporting tools like Tableau, Power BI, or Looker.
Programming and Frameworks
•    Advanced proficiency in Python, SQL, and Scala for data manipulation and processing.
•    Experience with infrastructure-as-code tools like Terraform or Cloud Formation.
•    Knowledge of big data technologies such as Apache Hadoop, Kafka, or Flink is a plus.
Soft Skills
•    Excellent problem-solving and analytical skills.
•    Strong written and verbal communication skills to effectively present complex concepts.
•    Ability to work in a fast-paced environment and manage multiple projects simultaneously.

Mandatory Competencies