Senior Data Engineer
Description
About Company:
Scripbox is a leading wealth management company with over 14 years of expertise and more than ₹23,000 crore in assets under management (AUM). We offer a comprehensive suite of wealth management solutions, including Mutual Fund Services (MFS), Registered Investment Advisor (RIA), and Portfolio Management Services (PMS), helping clients achieve their long-term financial goals.
As part of our growth journey, Scripbox has successfully acquired and integrated 10 companies since 2021, expanding our presence across eight office locations. Backed by Series D funding, we continue to scale rapidly, strengthen our wealth management capabilities, and deliver innovative, client-centric investment solutions across India.
Role Overview:
We are looking for a Senior Data Engineer to join Scripbox’s Data team and own critical data pipelines end-to-end—from source systems to business-critical reporting. This is a hands-on senior individual contributor role in a SEBI-regulated fintech environment, where data accuracy and reliability directly impact customer and business decisions. You will work with high autonomy alongside staff engineers and architects, contribute to technical decisions, and own significant parts of the data platform.
Key Responsibilities:
Data Pipelines: Design, build, and maintain DBT models and production pipelines with strong focus on idempotency, re-runnability, and safe backfills.
Python Ingestion: Build reliable ingestion workflows with watermarking, validation, and support for formats such as CSV, DBF, Parquet, and ZIP files. Airflow: Build and operate production DAGs, managing dependencies, failures, retries, and backfills.
Reliability: Own SLAs, monitoring, and incident response using tools such as Prometheus, Grafana, and Graylog; drive incidents to root cause.
Data Quality: Implement validation, anomaly detection, and automated pipeline-level checks. Data Governance: Implement RBAC/ABAC, PII masking, and audit controls aligned with retention requirements.
Databricks: Support the Unity Catalog migration and contribute to decisions around schemas, incremental models, and cluster strategy.
Engineering Standards: Follow coding, testing, and documentation standards; review PRs and collaborate with Product, Compliance, and BI teams.
Skills:
Must Have 5–9 years of hands-on Data Engineering experience with independent ownership of production pipelines. Strong SQL skills, including CTEs, window functions, incremental processing, and performance tuning at scale.
Strong DBT experience across models, macros, Jinja, incremental strategies, tests, and packages. Strong production experience with Airflow, including complex DAGs, dependency management, failure handling, and backfills.
Experience designing cloud data warehouses/lakehouses using Databricks, Redshift, BigQuery, or Snowflake. Strong Python skills for data engineering.
Good understanding of AWS, particularly S3, EC2, EKS, IAM, and Secrets Manager. Ability to write clear, structured, and referenceable technical specifications.
What We Offer :
Competitive salary with comprehensive benefits, including NPS, gratuity, and performance-based rewards that recognize your skills and contributions.
Performance-based variable pay and incentive programs (role-based), along with additional function-specific benefits where applicable.
Flexible work policies that support work-life balance while enabling collaboration and productivity.
Annual learning and development allowance to support your professional growth, continuous learning, and upskilling.
Clear career progression opportunities with exposure to challenging, high-impact work in a collaborative, inclusive, and innovation-driven environment.
Comprehensive health benefits.