FairMoney - Senior Data Engineer - ETL (8-10 yrs)

About the Role :

We are seeking a highly experienced and results-oriented Senior Data Engineer to join our expanding data team.

In this role, you will be a technical leader, responsible for designing, building, and maintaining robust and scalable data infrastructure that supports critical business initiatives.

You will leverage your extensive expertise in data engineering principles, cloud technologies, and data architecture to drive innovation and optimization within our data ecosystem.

Responsibilities :

Data Architecture and Design :

- Design and implement scalable and resilient data architectures, including data warehouses, data lakes, and data pipelines.

- Evaluate and select appropriate technologies and tools to meet business requirements.

- Develop and maintain data models, schemas, and metadata.

Data Pipeline Development and Optimization :

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

- Implement advanced ETL/ELT processes and data streaming solutions.

- Optimize data pipelines for performance, reliability, and cost-effectiveness.

- Implement data quality checks, and monitoring.

Cloud Data Platform Management :

- Design and manage cloud-based data platforms (AWS, Azure, GCP), including data storage, compute, and networking resources.

- Implement and maintain data security and access controls in cloud environments.

- Optimize cloud data infrastructure for performance and cost.

Data Governance and Quality :

- Establish and enforce data governance policies and procedures.

- Implement data quality monitoring and validation processes.

- Ensure compliance with data privacy regulations (e.g, GDPR, CCPA).

Technical Leadership and Mentorship :

- Provide technical leadership and mentorship to junior data engineers.

- Conduct code reviews and ensure adherence to coding standards and best practices.

- Drive innovation and continuous improvement within the data engineering team.

Collaboration and Communication :

- Collaborate with data scientists, data analysts, and business stakeholders to understand data requirements and deliver solutions.

- Communicate complex technical concepts to non-technical audiences.

- Lead technical discussions and presentations.

Automation and Infrastructure as Code (IaC) :

- Implement IaC using tools such as Terraform or CloudFormation.

- Automate deployment and management of data infrastructure.

- Contribute to CI/CD pipelines.

Required Skills and Experience :

- 8-10 years of experience in data engineering.

- Expert proficiency in SQL and experience with relational and NoSQL databases.

- Extensive experience with cloud-based data platforms (AWS, Azure, GCP).

- Strong experience with data warehousing and data lake technologies (e.g, Snowflake, Redshift, BigQuery, S3, Azure Data Lake).

- Expertise in ETL/ELT tools and technologies (e.g, Apache Airflow, Apache Spark, AWS Glue, Azure Data Factory).

- Proficiency in multiple programming languages (e.g, Python, Java, Scala).

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

- Strong understanding of data architecture principles and best practices.

- Experience with DevOps practices and CI/CD pipelines.

- Excellent problem-solving and analytical skills.

- Strong leadership and communication skills.

- Experience with IaC tools.

Preferred Qualifications :

- Experience with data governance and data quality tools.

- Experience with machine learning operations (MLOps).

- Experience with containerization and orchestration technologies (Docker, Kubernetes).

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

- Relevant certifications (e.g, AWS Certified Data Analytics Specialty, Azure Data Engineer Associate, Google Cloud Professional Data Engineer)