Recro.io - Data Architect - ETL/Python (10-12 yrs)

Role Overview :

We are looking for an experienced Data Architect to join our growing team in Bangalore.

The ideal candidate will have over 10 years of experience in Analytics Engineering, Data Architecture, or similar roles.

As a Data Architect, you will be responsible for designing and implementing scalable, reliable, and secure data architectures that empower the company to leverage its data efficiently for decision-making and analytics.

Key Responsibilities :

- Design and build robust, scalable data architectures that support the needs of various business units.

- Oversee the implementation of data pipelines, data warehouses, and data lakes to ensure optimal data storage, retrieval, and processing.

- Design architectures that can handle both batch processing and streaming/event-driven architectures to process large volumes of data in real-time and at scale.

- Work with cloud-based data platforms and tools such as AWS, Google Cloud Platform (GCP), and Microsoft Azure to design efficient data systems.

- Utilize modern data stack tools like Stitch/Fivetran, dbt/Dataform, Looker, and Tableau to streamline data integration, transformation, and visualization processes.

- Ensure data solutions are optimized for cloud data warehouses (e., BigQuery, Redshift, Snowflake) and aligned with the company's cloud-first strategy.

- Lead and mentor teams of data engineers, analysts, and architects to develop high-quality data models and systems.

- Foster a collaborative and growth-oriented environment, supporting the career development of your team members through coaching and mentoring.

- Promote the adoption of best practices in data engineering, analytics, and architecture across the organization.

- Collaborate with senior leadership to define and implement the company's data strategy, aligning with broader business goals.

- Lead the design and optimization of ETL processes, ensuring that data flows seamlessly from source to destination while maintaining consistency and integrity.

- Work with stakeholders to prioritize data initiatives, ensuring that business needs are met and aligned with the technology strategy.

- Ensure that data architecture aligns with data governance and security standards.

- Implement measures to ensure the privacy, security, and compliance of data, in line with regulatory requirements.

- Promote best practices for managing data quality, integrity, and lineage throughout the data lifecycle.

- 10+ years of experience in Analytics Engineering, Data Architecture, or related roles, with a proven track record of delivering complex data solutions.

- Proficiency in SQL and experience with modern data technologies such as Python, dbt, Fivetran, Looker, Tableau, Redshift, Snowflake, and BigQuery.

- Hands-on experience in both batch processing and real-time streaming/event-driven architectures (e., Kafka, Spark Streaming, etc.

- Expertise in designing and implementing data pipelines that can handle large volumes of data and enable business intelligence solutions.

- Proficient in cloud platforms such as AWS, Google Cloud, or Azure, including experience with data storage and processing solutions (e., S3, Redshift, BigQuery, Snowflake).

- Experience with data integration tools (e., Fivetran, Stitch) for automated ETL processes.

- Leadership experience: You've led teams of data engineers, architects, or analysts, driving successful project execution and fostering growth.

- Ability to mentor junior team members, guiding them through complex problems and technical challenges.

- Strong communication skills, with the ability to translate technical data concepts into understandable terms for senior leadership and stakeholders.

- You are a strategic thinker with the ability to see the big picture and make long-term decisions that align with business goals.

- Ability to understand business requirements and translate them into actionable data architectures.

- Excellent problem-solving and analytical skills, with the ability to solve complex technical challenges in data architecture