Data Engineer

Job Title:

Data Engineer

Location:

Lower Parel, Mumbai, MH
Work Mode:  Hybrid

About Us:

Join our dynamic and innovative startup skincare brand that is committed to redefining beauty standards with clean, effective, and sustainable products. Founded by beauty influencer Diipa Büller-Khosla, the brand emphasizes authenticity, and transparency, offering vegan and cruelty-free products that cater to diverse skin types while celebrating cultural heritage. We believe in empowering our customers with science-backed skincare solutions, and we’re looking for a visual storyteller with a passion for creating captivating content to help us take our brand to the next level.

Brand:

Role Overview
We are looking for a skilled and detail-oriented Data Engineer with 2–3 years of experience to build, maintain, and optimize scalable data pipelines and backend data infrastructure. This role will work closely with the team to ensure reliable, clean, and well-structured data is available for reporting, dashboards, and advanced analysis across multiple business functions.

Job Summary
We are looking for a skilled and detail-oriented Data Engineer with 2–3 years of experience to build, maintain, and optimize scalable data pipelines and backend data infrastructure. This role will work closely with the team to ensure reliable, clean, and well-structured data is available for reporting, dashboards, and advanced analysis across multiple business functions.

Key Responsibilities
Design, build, and maintain robust, scalable, and automated data pipelines (batch and, where applicable, near real-time).
Ingest data from multiple sources including APIs, flat files, databases, and third-party platforms.
Perform data cleaning, validation, transformation, and enrichment to ensure high data quality and consistency.
Manage and optimize data storage solutions such as data warehouses and data lakes (e.g., Big Query, Redshift, Snowflake).
Write efficient SQL queries and optimize performance for large datasets.
Implement data modeling best practices to support analytics and reporting use cases.
Monitor data pipelines, troubleshoot failures, and ensure high availability and reliability.
Collaborate with the analytics team to understand data requirements and translate them into technical solutions.
Maintain documentation for data pipelines, schemas, and workflows.
Ensure data security, access control, and compliance with internal standards.

Required

Skills & Qualifications
2–3 years of hands-on experience as a Data Engineer or in a similar backend data role.
Strong proficiency in SQL and experience working with large datasets.

Experience with at least one cloud data platform (GCP, AWS, or Azure).
Hands-on experience with data warehouses (e.g., Big Query, Redshift, Snowflake).
Experience building ETL/ELT pipelines using tools or frameworks such as Airflow, dbt, or custom Python-based pipelines.
Proficient in OLAP
Proficiency in Python for data processing and automation.
Solid understanding of data modeling concepts (fact tables, dimension tables, normalization vs denormalization).
Familiarity With ERP/SAP
Familiarity with version control systems (Git).
Strong problem-solving skills and attention to detail.

Good to Have

Experience with e-commerce, D2C, or marketplace data sources.
Exposure to streaming data tools (e.g., Pub/Sub, Kafka).
Experience working with BI tools such as Looker Studio, Power BI, or Tableau.
Understanding of basic Dev Ops concepts (CI/CD for data pipelines).

If this sounds like you – please share your updated resume on