Assistant Manager - Data Engineering

LatentView Analytics · Bangalore

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Last observed by our collector: 8 October 2026 at 11:39 pm IST. This is not a manual review or a confirmation from the employer.

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Collected role description

Designation : Assistant Manager - Data EngineeringLevel : L3Location : Bengaluru, Karnataka , India (BLR)Experience : 5 to 8 Years Job Role :We're looking for a Senior Data Engineer with strong data architecture and system designskills to design, build, and own end-to-end production pipelines powering analytics anddecision-making across the org. The role centers on deep Python + SQL expertise, robusttransaction-level fact tables, and rigorous data quality and auditability, ideally within a finance,risk, or compliance data domain. Internal candidates familiar with Uber's data platform stack(Piper/uWorc, Databook, uSecret, DSW, SourceGraph, Query Builder, OneETL) will beprioritized.<div> </div>Responsibilities : ● Own data architecture and system design decisions for pipelines and data models -grain, partitioning, schema evolution, and scalability tradeoffs.● Take end-to-end ownership of pipelines in production: design, build, deploy, monitor,and operate.● Design and build transaction tables (append-only, immutable event/transaction-grain facttables) alongside standard fact/dimension models using medallion (bronze/silver/gold)architecture.● Build and support pipelines for finance, risk, or compliance use cases whereaccuracy, auditability, and data lineage are critical.● Implement data quality and auditability controls: validation checks, reconciliationlogic, anomaly detection, and audit trails for every pipeline you own.● Write complex, cross-dialect SQL (MySQL + PostgreSQL): window functions,multi-layered CTEs, CASE-driven logic, COALESCE/NULLIF, type casting, anddate/timestamp handling.● Build idempotent reload patterns (DELETE+INSERT), UNION ALL/set operations, andtemplated (Jinja-style) SQL including handling for late-arriving/corrected transactionrecords without double-counting.● Orchestrate Airflow-style DAGs (Pipeline/BaseTask, ExternalTaskSensor forcross-pipeline deps) with secure credential handling via uSecret.● Build Python ETL tooling: pandas (CSV ↔ DB), SQLAlchemy + raw drivers (MySQLdb,psycopg2), type hints/dataclasses, class-based pipeline design.● Integrate with Google Drive/Sheets APIs; build YAML-driven pipeline configs; handlePiper staging/user_staging quirks.● Own CI/CD for pipelines via standard Git workflows.● Use Uber's internal stack day-to-day: OneETL for pipeline authoring, Piper/uWorc forscheduling, Databook for lineage, uSecret for credentials, DSW notebooks for CSV/tablework, SourceGraph for code search, Query Builder for ad hoc SQL Required skills : Primary Skills: Data Engineering, Data Architecture & System Design, Data Modeling (Fact/Dim, Medallion), Expert SQL, Advanced Python, Workflow Orchestration (Airflow), Data Quality & Auditability, Financial/Risk/Compliance Data.Secondary Skills: Hive/Hadoop, Cross-dialect SQL (MySQL/PostgreSQL), Data Lineage & Reconciliation, Production Support & Monitoring.<span style="font-size:14px;font-family:Georgia;color:rgb(42,51,62);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap;">We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status.

Collected experience requirement

6 - 8 Years