Senior Engineering Intelligence Analyst
New
J
JobgetherData Engineering
IndiaFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5 to 8 years
- Required Skills
- PythonSQLAgileETLRESTful APIsData modelingLooker
Requirements
- 5 to 8 years of experience in analytics engineering, data engineering, business intelligence, or a related technical analytics role.
- Expert-level proficiency in SQL, including complex joins, window functions, common table expressions (CTEs), and query optimization.
- Strong Python programming skills with experience building data processing pipelines, automation scripts, and ETL/ELT workflows.
- Hands-on experience designing advanced dashboards and semantic data models using Looker and LookML.
- Experience integrating REST APIs and building scalable data pipelines across multiple enterprise systems.
- Solid understanding of software development lifecycle (SDLC), Agile methodologies, and engineering delivery processes.
- Experience working with cloud-based data platforms, preferably Google BigQuery, along with strong knowledge of data modeling, governance, and performance optimization.
- Familiarity with engineering tools such as Jira, Jira Structure, Jellyfish, Salesforce, or similar engineering management platforms.
- Knowledge of engineering performance metrics, including DORA metrics, flow efficiency, cycle time, throughput, and related operational KPIs.
- Strong analytical thinking, communication, and stakeholder management skills.
Responsibilities
- Design, develop, and maintain interactive business intelligence dashboards that provide visibility into engineering performance, portfolio health, delivery forecasts, and resource utilization.
- Build and optimize scalable data pipelines by integrating data from multiple enterprise platforms, APIs, and cloud data sources to create reliable, automated analytics workflows.
- Develop and maintain efficient data models that establish trusted, centralized engineering metrics while ensuring data quality, consistency, and governance.
- Write high-performance SQL queries and Python scripts to extract, transform, validate, and automate large datasets for reporting and analysis.
- Implement monitoring, alerting, and anomaly detection capabilities to proactively identify delivery risks, resource constraints, and operational issues.
- Partner with engineering, product, and business stakeholders to gather requirements, translate business needs into technical solutions, and deliver executive-ready analyses.
- Document data lineage, reporting logic, and metric definitions to ensure transparency, scalability, and long-term maintainability of analytics solutions.
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