Data Architect

7 days ago

Delhi, Delhi, India MOBILLOR TECHNOLOGIES PRIVATE LIMITED Full time

About the Role :

We are seeking a highly experienced and motivated Data Architect to join our dynamic team in Bangalore. In this critical role, you will be responsible for designing, building, and maintaining our robust and scalable data infrastructure on AWS. You will leverage your deep expertise in AWS services, data modeling, and data engineering to architect high-performance data lakes and data warehouses that support our growing business needs. You will be a key driver in ensuring data quality, governance, and lineage, and will play a pivotal role in shaping our overall data strategy.

Responsibilities :

Architect and Design Data Solutions :

- Design and implement scalable and efficient data architectures on AWS, focusing on high throughput data lakes and data warehouses.

- Develop comprehensive data models, including medallion architecture and star schema, to support diverse analytical and reporting requirements.

- Define and enforce data standards, policies, and procedures to ensure data consistency and quality.

AWS Data Ecosystem Expertise :

- Lead the development and optimization of PySpark-based data pipelines for data ingestion, transformation, and processing.

- Utilize the AWS Glue ecosystem (Glue Jobs, Data Catalog, Bookmarks, Schema Registry, Crawlers) to build and manage a robust data catalog and ETL/ELT processes.

- Design and implement data workflows using Airflow, AWS Step Functions, or Glue Workflows for automated data processing and orchestration.

- Optimize data storage and retrieval using Parquet and Iceberg file formats, including partitioning, snapshotting, and performance tuning.

- Implement and manage data lineage, data governance, and data quality solutions using AWS services like Glue Data Quality, Deequ, Great Expectations (GE), and Lake Formation.

Data Integration and Management :

- Design and implement Change Data Capture (CDC) mechanisms using tools like Debezium or AWS DMS.

- Manage and optimize data warehousing solutions, preferably with experience in Amazon Redshift.

- Ensure data security and compliance with relevant regulations and industry best practices.

Collaboration and Communication :

- Collaborate with data engineers, data scientists, and business stakeholders to understand data requirements and translate them into technical solutions. -

- Provide technical leadership and mentorship to junior team members.

- Communicate complex technical concepts effectively to both technical and non-technical audiences.

- Document all architecture and process for proper knowledge transfer.

Continuous Improvement :

- Stay up-to-date with the latest AWS data services and technologies.

- Identify and implement opportunities for performance optimization and cost reduction.

- Proactively address data-related challenges and propose innovative solutions.

Required Skills and Experience :

- Minimum of 10+ years of experience in data architecture and data engineering.

- Extensive experience with AWS data services, including :

- PySpark for building high-throughput data lakes.

- AWS Glue ecosystem (Glue Jobs, Data Catalog, Bookmarks, Schema Registry, Crawlers).

- Workflow orchestration tools (Airflow, AWS Step Functions, Glue Workflows).

- Data modeling techniques (medallion architecture, star schema).

- Parquet and Iceberg file formats (optimization, partitioning, snapshotting).

- Data lineage, data governance, and data quality (Glue Data Quality, Deequ, GE, Lake Formation).

- Amazon Redshift (nice to have).

- CDC tools like Debezium and DMS.

- Strong understanding of data warehousing principles and best practices.

- Experience with data integration and ETL/ELT processes.

- Excellent problem-solving and analytical skills.

- Strong communication and collaboration skills.

- Bachelor's or Master's degree in Computer Science, Information Technology, or a related field. -

- AWS Certified Data Engineer - Associate or Professional (Preferred).

Desired Skills :

- Experience with other cloud platforms (e.g., Azure, GCP).

- Experience with real-time data streaming technologies (e.g., Kafka, Kinesis).

- Experience with data visualization tools (e.g., Tableau, Power BI).

- Knowledge of Data mesh architecture

(ref:hirist.tech)

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