Data Architect

Good co India; United States; Remote; USD 130,000 - 190,000; Full time

Job summary

Good co India is seeking an experienced Data Architect to design and lead enterprise data architectures across cloud platforms and analytics ecosystems. You will translate business needs into scalable data models, pipelines, and integrations while enforcing governance, security, and cost efficiencies.

The role requires strong SQL, data modeling, and cloud experience (AWS/Azure/GCP) with a track record of data modernization and mentoring technical teams.

Qualifications

• 5+ years in data engineering, data architecture, BI, or enterprise data management.
• Proven experience designing enterprise-scale data architectures and platforms.
• Strong expertise in data modeling, data warehousing, data lakes, and lakehouse architectures.
• Advanced SQL and experience with relational databases.
• Experience with cloud data platforms (AWS, Azure, GCP) and modern data tech stack.

Responsibilities

• Design and lead scalable, secure data architectures aligned with business objectives.
• Define data architecture strategies, standards, roadmaps, and governance practices.
• Translate requirements into data models, platforms, integrations, and technical solutions.
• Design data warehouses, data lakes, lakehouses, and cloud-based platforms.
• Develop logical/physical/conceptual data models and ETL/ELT pipelines.
• Architect data integration across databases, apps, APIs, and cloud services.
• Establish data governance, quality, lineage, metadata, and master data management.
• Design secure architectures with access controls, encryption, and privacy controls.
• Optimize platforms for performance, scalability, availability, and cost.
• Lead data migrations, modernization, and cloud transformation initiatives.
• Evaluate data technologies and architectural patterns; mentor teams.
• Collaborate with data engineers, software engineers, BI, data scientists, security, and stakeholders.
• Conduct architecture reviews, technology assessments, and performance evaluations.
• Maintain documentation and standards for data integration, storage, and lifecycle.

Skills

Architectural leadership

Analytical thinking

Stakeholder management

Education

Bachelor's degree in CS/IT/Data Science/related field

Master's degree advantageous

Relevant certifications (AWS Data Engineer / Google Professional Data Engineer / Azure Data Engineer / Databricks / Snowflake / DAMA CDMP)

Tools

PostgreSQL

MySQL

SQL Server

Oracle

MongoDB

Cassandra

DynamoDB

AWS

Azure

GCP

Snowflake

Databricks

BigQuery

Redshift

Azure Synapse

Apache Spark

Kafka

Airflow

dbt

Power BI

Tableau

Job description

Role & responsibilities

• Design and lead enterprise data architectures that are scalable, secure, reliable, and aligned with business objectives.
• Define data architecture strategies, standards, principles, and technology roadmaps.
• Translate business requirements into data models, data platforms, integration architectures, and technical solutions.
• Design and implement data warehouses, data lakes, lakehouses, and modern cloud-based data platforms.
• Develop logical, physical, conceptual, and dimensional data models.
• Design batch and real-time data pipelines using ETL/ELT and streaming technologies.
• Architect data integration solutions across databases, applications, APIs, cloud platforms, and third-party systems.
• Establish data governance, data quality, metadata management, data lineage, and master data management practices.
• Design secure data architectures incorporating access controls, encryption, privacy, compliance, and data-protection standards.
• Optimize data platforms for performance, scalability, availability, reliability, and cost efficiency.
• Lead data migration, modernization, and cloud transformation initiatives.
• Evaluate and recommend data technologies, tools, platforms, and architectural patterns.
• Collaborate with data engineers, software engineers, BI teams, data scientists, cloud teams, security, and business stakeholders.
• Conduct architecture reviews, data-model reviews, technology assessments, and performance evaluations.
• Establish standards for data integration, storage, processing, retention, and lifecycle management.
• Ensure data platforms support analytics, reporting, machine learning, and real-time business requirements.
• Maintain data architecture documentation, data models, lineage diagrams, technical specifications, and standards.
• Mentor data engineers and architects and provide technical leadership across data initiatives.

Preferred candidate profile

• 5 to 10 years of experience in data engineering, database development, data architecture, BI, or enterprise data management.
• Proven experience designing and implementing enterprise-scale data architectures and platforms.
• Strong expertise in data modeling, dimensional modeling, data warehousing, data lakes, and lakehouse architectures.
• Advanced SQL skills and strong experience with relational databases such as PostgreSQL, MySQL, SQL Server, or Oracle.
• Experience with NoSQL databases such as MongoDB, Cassandra, DynamoDB, or similar technologies.
• Hands-on experience with cloud data platforms such as AWS, Azure, or GCP.
• Experience with modern data platforms and technologies such as Snowflake, Databricks, BigQuery, Redshift, or Azure Synapse.
• Strong knowledge of ETL/ELT, data integration, batch processing, and real-time/streaming architectures.
• Experience with Apache Spark, Kafka, Airflow, dbt, or similar data engineering technologies.
• Strong understanding of data governance, data quality, metadata, data lineage, master data management, and data security.
• Experience designing secure and compliant data architectures with appropriate access controls, encryption, and privacy mechanisms.
• Knowledge of BI and analytics platforms such as Power BI, Tableau, or equivalent tools.
• Experience leading data migration, modernization, cloud adoption, and large-scale data transformation projects.
• Strong understanding of distributed systems, scalability, performance optimization, and cloud cost management.
• Strong analytical, problem-solving, communication, documentation, and stakeholder-management skills.
• Ability to provide technical leadership and mentor data engineers and development teams.
• Bachelor's degree in Computer Science, Information Technology, Data Science, Computer Engineering, Statistics, Mathematics, or a related field; Master's degree is an advantage.
• Relevant certifications such as AWS Data Engineer, Google Professional Data Engineer, Microsoft Azure Data Engineer, Databricks, Snowflake, or DAMA CDMP are preferred.