About Mitra

Mitra AI is a global technology company that specializes in AI-driven solutions, cloud engineering, enterprise integration and workflow automation. Headquartered in the UK, Mitra has been serving global clients for the last 12 years in the US, UK, EU and APAC, across industries such as BFSI, telecommunications, healthcare, and retail, helping businesses modernize and optimize their operations.

About the Role:

We are seeking an experienced Data Engineer with 3/ 4 years of experience to join our Compliance Technology Engineering team. Working closely with business and technology experts, you’ll collaborate within a skilled peer network across our Risk Management Group (RMG). Your role will focus on delivering technical capabilities to support business and compliance goals, ensuring a high-performance and stable platform that meets the needs of both internal and external stakeholders.

Key Responsibilities:

Collaborate with data architects and data modelers, performing independent data analysis and data modeling.

Excel in data preparation and integration, designing, developing, and refining data models while resolving performance issues.

Exhibit meticulous attention to technical design strategy.

Manage stakeholder engagement effectively across multiple levels.

Proactively communicate and collaborate with team members.

Conduct downstream analysis and understand end-to-end data flow, especially in multi-system environments.

Translate technical requirements for non-technical audiences and vice versa. • Work within an Agile delivery framework.

Preferred Qualifications:

Bachelor’s degree in a quantitative field, such as Computer Science or Engineering.

Minimum 3 years of hands-on experience with working with Big data or data processing specifically in ETLs, Data specific tools & SQL.

Knowledge of data engineering aspects in governance, data quality, and control frameworks.

Analytical and creative approach to using data and insights to identify new opportunities, root causes, and risks.

Core Skills:

Advanced data engineering expertise with Spark, SQL, Python, and Airflow.

Strong understanding of big data querying tools.

Experience with data warehousing platforms, particularly AWS Redshift.

Knowledge of data architecture, access patterns, and data modeling principles and ETL Frameworks.

Proficient in data quality measurement and monitoring.

Competence in managing metadata, including control totals and checksums for data load assurance.

Ownership mindset for issue resolution.

Familiarity with AWS cloud services, including EC2, S3, IAM, EKS, RDS, and Linux.

Experience with DevOps methodologies and CI/CD tools.

Strong foundation in Data Warehousing/ETL concepts.

Optional but Desirable:

Experience with event-based and message-driven distributed systems, such as Kafka or Solace.