Job
Description
You will be working at Paras Twin Tower, Gurgaon as a full-time employee for Falcon, a Series-A funded cloud-native, AI-first banking technology & processing platform. Falcon specializes in assisting banks, NBFCs, and PPIs to efficiently launch cutting-edge financial products like credit cards, credit lines on UPI, prepaid cards, fixed deposits, and loans. Since its inception in 2022, Falcon has processed over USD 1 billion in transactions, collaborated with 12 of India's top financial institutions, and generated revenue exceeding USD 15 million. The company is supported by prominent investors from Japan, the USA, and leading Indian ventures and banks. To gain more insights about Falcon, visit https://falconfs.com/. As an Intermediate Data Engineer with 5-7 years of experience, your responsibilities will include designing, developing, and maintaining scalable ETL processes using open source tools and data frameworks such as AWS Glue, AWS Athena, Redshift, Apache Kafka, Apache Spark, Apache Airflow, and Pentaho Data Integration (PDI). You will also be accountable for designing, creating, and managing data lakes and data warehouses on the AWS cloud, optimizing data pipeline architecture, formulating complex SQL queries for big data processing, collaborating with product and engineering teams to develop a platform for data modeling and machine learning operations, implementing data structures and algorithms to meet functional and non-functional requirements, ensuring data privacy and compliance, developing processes for monitoring and alerting on data quality issues, and staying updated with the latest data engineering trends by evaluating new open source technologies. To qualify for this role, you must have a Bachelor's or Master's degree in Computer Science or MCA from a reputable institute, at least 4 years of experience in a data engineering role, proficiency in Python, Java, or Scala for data processing (Python preferred), a deep understanding of SQL and analytical data warehouses, experience with database frameworks like PostgreSQL, MySQL, and MongoDB, knowledge of AWS technologies such as Lambda, Athena, Glue, and Redshift, experience implementing ETL or ELT best practices at scale, familiarity with data pipeline tools like Airflow, Luigi, Azkaban, dbt, proficiency with Git for version control, familiarity with Linux-based systems, cloud services (preferably AWS), strong analytical skills, and the ability to work in an agile and collaborative team environment. Preferred skills for this role include certification in any open source big data technologies, expertise in Apache Hadoop, Apache Hive, and other open source big data technologies, familiarity with data visualization tools like Apache Superset, Grafana, Tableau, experience in CI/CD processes, and knowledge of containerization technologies like Docker or Kubernetes. If you are someone with these skills and experience, we encourage you to explore this opportunity further. Please note that this job description is for an Intermediate Data Engineer role with key responsibilities and qualifications outlined.,
