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Data Architect

2 months ago

Chennai, India Peninsular Research Operation Full time

JOB DESCRIPTION: Data Architect

REPORTS TO: Head of Engineering

ROLE OVERVIEW

As the Data Architect, you will lead the design and implementation of a robust, scalable data platform that supports our business's growing needs. You will work closely with engineering, product, and analytics teams to create data strategies that ensure the security, integrity, and accessibility of data. You will be the gatekeeper of all things data, advocating for best practices in data governance, architecture, and engineering while ensuring data becomes an integral part of our organizational culture.

KEY RESPONSIBILITIES

  • Data Strategy & Roadmap: Develop and implement a comprehensive data architecture strategy that aligns with the company’s goals, ensuring scalability, security, and high availability.
  • Data Platform Development: Architect, design, and oversee the implementation of data pipelines, data warehouses/lakes/mesh, and BI infrastructure to support business intelligence, analytics, and reporting needs.
  • Data Governance: Establish and enforce data governance frameworks, ensuring data quality, integrity, and security across all platforms and processes.
  • Collaboration: Work with cross-functional teams (product, engineering, data science, etc.) to understand data needs, provide technical leadership, and recommend data-driven solutions.
  • Data Integration: Design and manage the integration of data from various sources, ensuring seamless data flow across the organization and external partners.
  • Methodologies & Best Practices: Champion data best practices, including versioning, documentation, and model management, and enhance methodologies to make data a core asset of the organization.
  • Technology Evaluation: Evaluate and recommend data-related technologies, tools, and platforms (e.g., databases, ETL tools, cloud services) to improve data processing, storage, and accessibility.
  • Scalability: Anticipate the company’s data growth and design solutions that accommodate both current and future data needs, including scaling for big data and real-time analytics.
  • Compliance: Ensure that data practices comply with relevant regulations (e.g., GDPR, CCPA) and industry standards.

REQUIRED SKILLS & QUALIFICATIONS:

Technical Expertise:

  • Proven experience in data architecture, data engineering, or a related field, ideally within high-growth tech environments (social media, e-commerce, etc.)
  • Hands-on experience with designing and building large-scale data platforms, including data lakes, data warehouses, and data pipelines
  • Proficiency with cloud-based data technologies (e.g., AWS, Google Cloud, Azure) and related services (e.g., Redshift, Big Query, Databricks, Snowflake)
  • Strong knowledge of database systems (SQL and NoSQL) and data modeling techniques
  • Experience with ETL/ELT tools and frameworks (e.g., Apache Airflow, Apache Spark, Apache NiFi, Talend)
  • Expertise in designing for both structured and unstructured data storage and processing (e.g., batch and real-time streaming data)
  • Familiarity with data visualization and BI tools (e.g., Looker, Tableau, Power BI).
  • Familiarity with machine learning and AI applications, and their integration into data platforms.
  • Experience with real-time analytics and event-driven architecture (e.g., Apache Kafka, AWS Kinesis).
  • Strong programming skills in languages such as Python, Scala, or Java

Data Governance & Security:

  • Deep understanding of data governance frameworks, data quality management, and data security best practices.
  • Experience with implementing role-based access controls, encryption, and auditing practices to ensure data security and compliance.

Strategic Thinking & Leadership:

  • Ability to align data architecture with business strategy, translating business goals into a data roadmap.
  • Strong problem-solving skills and the ability to think strategically about data from both a technical and business perspective.
  • Proven leadership in promoting data-driven decision-making and fostering a culture that values data as a strategic asset.

Collaboration & Communication:

  • Excellent communication skills, with the ability to translate complex technical concepts into understandable language for non-technical stakeholders.
  • Experience working in cross-functional teams and collaborating with a wide range of stakeholders, including product, engineering, data science, and leadership teams.