ernakulam kerala network support engineer Jobs – 62 Open Jobs Today

Data Architect
GadgEon —Kochi, Kerala
- Azure
- Computer Science
- Master's degree

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Data Architect

GadgEon -
Kochi, Kerala

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Job details

Qualifications

Data modeling
Azure
Computer Science
Spark
Encryption
Microsoft SQL Server
Information Systems
Master's degree
AWS
Bachelor's degree
PostgreSQL
Scalability
Kafka
Metadata
Redshift
AI
Leadership
Communication skills
MySQL
Analytics

Full job description

Joining Gadgeon offers a dynamic and rewarding
career experience that fosters both personal and
professional growth. Our collaborative culture
encourages innovation, empowering team members
to contribute their ideas and expertise to
cutting-edge projects.

A technically strong embedded professional who can own architecture decisions, work across domains, and lead embedded development teams.

Data Architect

The Data Architect is responsible for designing scalable, secure, and efficient data architectures across on-premises, cloud, and hybrid environments. This role focusses on conceptual and logical design, data modelling, integration patterns, migration strategies, governance, and enabling analytics/AI.

The role collaborates with engineering teams and customer technical stakeholders to translate business requirements into robust data platform designs.

Key duties/ responsibilities

Design end-to-end data architectures covering ingestion, storage, transformation, governance, and consumption layers.
Define data modeling approaches (conceptual, logical, physical) aligned to business needs for operational, analytical, and AI/ML use cases.
Architect data flows and integration patterns across on-prem systems, cloud platforms, legacy environments, and modern pipelines using tools like dbt,
Airbyte, Airflow, Glue, Dataflow, Databricks, Spark, Flink, Kafka/Kinesis/PubSub
Develop ingestion and transformation designs using batch, micro-batch, streaming, or CDC patterns as applicable.
Establish standards for metadata, lineage, quality, and governance across diverse customer environments.
Define secure data movement strategies, including network boundaries, access control, encryption, and compliance considerations.
Provide architecture guidance to engineering teams during implementation, including reviews of models, pipelines, and data structures.
Conduct technical workshops with customers to understand data landscapes, constraints, and integration requirements.
Ensure data architectures support analytics, BI, self-service, and AI/ML workloads effectively.
Document high-level and low-level designs, patterns, and architectural decisions clearly and comprehensively.

Leadership Skills:

Ability to lead architectural discussions and guide engineering teams with clarity and rationale behind design choices.
Strong stakeholder communication skills to interface with customer architects, product teams, and internal engineering units.
Demonstrated capability to simplify complex problems and present solution options effectively.
Proactive in identifying risks, trade-offs, and long-term implications in data platform design.
Mentorship mindset toward enabling engineers to adopt best practices and architectural standards.

Required Technical Skills:

Strong foundation in data modeling, including normalized, dimensional, and domain-oriented models.
Deep understanding of data architecture principles, distributed data systems, and platform scalability.
Experience designing solutions in hybrid environments involving on-prem systems, cloud platforms, and legacy data technologies.
Expertise in ingestion and transformation design, covering batch, streaming, CDC, and event-driven patterns.
Knowledge of data governance, metadata management, lineage, quality frameworks, and lifecycle management.
Understanding of security, compliance, and privacy considerations for data movement and storage.
Familiarity with supporting analytics, dashboards, semantic layers, and AI/ML pipelines from an architectural perspective.
Ability to evaluate technology options (cloud, on-prem, open-source, commercial) and recommend appropriate architectural approaches.
Experience with modern relational and analytical data engines and their architectural considerations (eg. PostgreSQL, Microsoft SQL Server, MySQL, ClickHouse, and cloud-native warehouses (e.g., Snowflake, BigQuery, Redshift, Synapse)).

Qualification:

Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Engineering, or a related field.
8–15 years of experience in data engineering and data architecture roles.
Experience working with customers across diverse technology landscapes (on-prem, cloud, hybrid).
Certifications in AWS/GCP/Azure/Snowflake/Databricks preferred.
Exposure to modernization of legacy data systems, data warehouses, and ETL ecosystems is an added advantage.

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