Falcon a Series-A funded cloud-native, AI-first banking technology & processing platformthat helps banks, NBFCs, and PPIs quickly and affordably launch next-gen financialproducts, such as credit card, credit line on UPI, prepaid card, fixed deposits, and loans.Since our 2022 launch, we’ve processed USD 1 Bn+ in transactions, signed on 12 of India'stop financial institutions, & clocked USD 15 Mn+ in revenue. Our company is backed bymarquee investors from around the world, including heavyweight investors from Japan,USA, as well as leading Indian ventures and banks.For more details, please visit https://falconfs.com/Experience level : Intermediate (5 - 7 years)

Key Responsibilities

Design, develop, and support scalable ETL processes using open source tools and data

frameworks like AWS Glue, AWS Athena, redshift, Apache Kafka, Apache Spark, Apache Airflow and
Pentaho Data IntegrationPDI

Design, creation and maintenance of data lakes and data warehouse on AWS cloud.
Maintain and optimise our data pipeline architecture, and formulate complex SQL queries for big

data processing.

Collaborate with product and engineering teams to design and develop a platform for data

modelling and machine learning operations.

Implement various data structures and algorithms to ensure we meet both functional and

non-functional requirements.

Maintain data privacy and compliance according to industry standards.
Develop processes for monitoring and alerting on data quality issues.
Continually evaluate new open source technologies and stay updated with the latest data

engineering trends.

Key Qualifications

Bachelor’s or Master’s degree in Computer Science, MCA from a reputed institute
Minimum of 4 years experience in a data engineering role.
Experience using Python, Java, or Scala for data processing (Python preferred)
Demonstrably deep understanding of SQL and analytical data warehouses.
Solid experience with popular database frameworks such as PostgreSQL, MySQL, and MongoDB
Knowledge of AWS technologies like , lambda, Athena, glue and redshift
Hands-on experience implementing ETL (or ELT best practices at scale.
Hands-on experience with data pipeline tools (Airflow, Luigi, Azkaban, dbt)
Experience with version control tools like Git.
Familiarity with Linux-based systems and cloud services, preferably in environments like AWS.
Strong analytical skills and ability to work in an agile and collaborative team environment.

Preferred Skills

Certification in any open source big data technologies.
Expertise in open source big data technologies like Apache Hadoop, Apache Hive, and others.
Familiarity with data visualisation tools like Apache Superset, Grafana, tableau etc.
Experience in CI/CD processes and containerization technologies like Docker or Kubernetes.

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