Data Engineer cum Analyst
maneuvermarketing
Job Description
1. Data Infrastructure & Pipeline Reliability
Keep data flowing accurately, on time, and at cost.
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Monitor, build, and respond to Daton pipeline alerts; track latency, freshness, and completeness across all source systems
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Investigate pipeline failures and perform root cause analysis at the pipeline, QC/validation, and API/source system level
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Create and enhance data pipelines; onboard new platform integrations and implement logic changes to existing ones
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Coordinate with source system owners and vendors when issues originate upstream
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Optimize query performance and warehouse costs; implement table partitioning, clustering, and incremental load strategies
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Maintain documentation for all pipeline logic, schema changes, and incidents, with a continuously updated change log
2. Data Quality & Validation
Build and maintain the quality layer that makes data trustworthy across the organization.
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Design and maintain automated QC checks: null checks, duplicate detection, range/boundary checks, valid value checks, referential integrity, and business-logic validations for key KPIs
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Perform daily validation of critical metrics against source UIs (Shopify, GA4, Meta, Klaviyo, Google Ads, Loop, etc.)
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Ensure KPI consistency across raw, transformed, and reporting layers
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Implement anomaly detection for key tables and metrics
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Proactively flag and resolve data integrity issues across teams
3. Reporting & Dashboard Ownership
Own the company-wide reporting infrastructure.
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Build, maintain, and evolve dashboards and KPI trackers for Growth, Marketing, Product, Finance, and Operations
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Design and manage executive-level dashboards that support leadership decision-making
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Own metric definitions, documentation, and reporting standards across the organization
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Leverage dbt (or equivalent) to maintain clean, reliable analytical layers
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Use AI tools and automation to improve reporting efficiency and reduce manual effort
4. Growth & Marketing Analytics
Be the analytical partner the Growth team relies on.
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Analyze performance across paid media channels — CAC, ROAS, MER, LTV, retention, and contribution margin
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Conduct deep-dive analyses to identify growth opportunities and performance drivers
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Evaluate promotional performance and measure the impact of marketing initiatives
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Support experimentation and A/B testing: help design tests, interpret results, and communicate outcomes to stakeholders
5. Product & Commercial Analysis
Turn data into commercial decisions.
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Monitor and evaluate product performance across SKUs, channels, and markets
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Analyze purchasing patterns, customer segmentation, pricing impact, and promotional effectiveness
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Provide recommendations based on quantitative analysis and business impact
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Identify opportunities to improve product assortment, pricing decisions, and inventory allocation
6. Ad-Hoc Analysis & Decision Support
Respond fast and think clearly under ambiguity.
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Answer analytical requests from cross-functional teams with structured, business-ready outputs
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Investigate business challenges, identify root causes, and present actionable recommendations
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Translate complex datasets and quantitative findings into clear narratives for non-technical stakeholders
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Coordinate and manage VAs on data-related tasks — scoping work, reviewing outputs, maintaining quality
7. Security, Compliance & Access Management
Protect data and maintain regulatory alignment.
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Maintain GDPR, CCPA, and related compliance controls
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Manage RBAC and column-level security in BigQuery; ensure PII masking and access restrictions
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Respond to security incidents related to data access or credentials
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