SDE 2 (Data Engineering)

SDE 2 Data Platform Engineer

We are looking for a strong and hands-on SDE 2 Data Engineering to contribute to the design, development, and scaling of our data infrastructure. The role requires solid technical expertise in building reliable data pipelines, working with big data technologies, and ensuring high-quality data delivery. You will work closely with senior engineers and cross-functional teams to build scalable data systems that support analytics, reporting, and business operations at Licious.

Ideal Experience: 2 - 5 yrs

What Youll Do

Core Engineering Responsibilities

• Develop and maintain scalable ETL/ELT data pipelines and data processing workflows.
• Contribute to design discussions, provide code reviews, and ensure high-quality engineering practices.
• Implement real-time and batch data processing solutions using technologies such as Spark, Flink, Kafka, or Debezium.
• Ensure data quality, observability, lineage, and monitoring across pipelines.

Data Infrastructure & Architecture

• Participate in building and optimizing data platforms that support high-volume and high-velocity data.
• Contribute to architectural decisions under the guidance of senior engineers and architects.
• Implement best practices around data modeling, partitioning, indexing, and performance optimization.

Collaboration & Cross-team Work

• Work with product, analytics, and ML teams to understand data requirements and deliver reliable data assets.
• Collaborate with DevOps and platform teams to ensure efficient, scalable, and cost-optimized deployments.

What Youll Bring

Technical Skills

• Hands-on experience with big data technologies:
• Batch & Stream Processing: Spark, Flink, Kafka, Debezium.
• Warehousing & Analytics: Redshift, Snowflake, ClickHouse, Hive, Hudi, Iceberg, or Databricks.
• Orchestration: Airflow, Azkaban, or Luigi.
• Strong SQL expertise (MySQL/PostgreSQL) and familiarity with NoSQL systems like MongoDB or Cassandra.
• Working knowledge of AWS services such as S3, EC2, EMR, Glue, RDS, Redshift, Lambda, MSK, or SQS.
• Proficiency in Python, Scala, or Java for building data applications.
• Understanding of software engineering fundamentals CI/CD, testing, version control.

Soft Skills

• Strong problem-solving skills with the ability to take ownership of components.
• Ability to work independently and collaborate effectively with cross-functional teams.
• Eagerness to learn, adapt, and grow towards higher technical responsibilities.

Preferred Qualifications

• Experience with data lakehouse architectures.
• Familiarity with Docker or Kubernetes.
• Exposure to data observability or MLOps frameworks.
• Experience working in fast-paced or consumer-tech environments.