Responsibilities:

● Design, build, and optimize data pipelines to ingest, process, transform, and load data from

various sources into our data platform

● Implement and maintain ETL workflows using tools like Debezium, Kafka, Airflow, and Jenkins to

ensure reliable and timely data processing

● Develop and optimize SQL and NoSQL database schemas, queries, and stored procedures for

efficient data retrieval and processing

● Work with both relational databases (MySQL, PostgreSQL) and NoSQL databases (MongoDB,

DocumentDB) to build scalable data solutions

● Design and implement data warehouse solutions that support analytical needs and machine

learning applications

● Collaborate with data scientists and ML engineers to prepare data for AI/ML models and

implement data-driven features

● Implement data quality checks, monitoring, and alerting to ensure data accuracy and reliability

● Optimize query performance across various database systems through indexing, partitioning,

and query refactoring

● Develop and maintain documentation for data models, pipelines, and processes

● Collaborate with cross-functional teams to understand data requirements and deliver solutions

that meet business needs

● Stay current with emerging technologies and best practices in data engineering

Requirements:

● 6+ years of experience in data engineering or related roles with a proven track record of building

data pipelines and infrastructure

● Strong proficiency in SQL and experience with relational databases like MySQL and PostgreSQL

● Hands-on experience with NoSQL databases such as MongoDB or AWS DocumentDB

● Expertise in designing, implementing, and optimizing ETL processes using tools like Kafka,

Debezium, Airflow, or similar technologies

● Experience with data warehousing concepts and technologies

● Solid understanding of data modeling principles and best practices for both operational and

analytical systems

● Proven ability to optimize database performance, including query optimization, indexing

strategies, and database tuning

● Experience with AWS data services such as RDS, Redshift, S3, Glue, Kinesis, and ELK stack

● Proficiency in at least one programming language (Python, Node.js, Java)

● Experience with version control systems (Git) and CI/CD pipelines

● Bachelor's degree in Computer Science, Engineering, or related field

Job Description

Preferred Qualifications:

● Experience with graph databases (Neo4j, Amazon Neptune)

● Knowledge of big data technologies such as Hadoop, Spark, Hive, and data lake architectures

● Experience working with streaming data technologies and real-time data processing

● Familiarity with data governance and data security best practices

● Experience with containerization technologies (Docker, Kubernetes)

● Understanding of financial back-office operations and FinTech domain

● Experience working in a high-growth startup environment

● Master's degree in Computer Science, Data Engineering, or related field