Data Engineer

شرح موقعیت

Data Engineer (AI-Enabled BI & Analytics) We are looking for a Data Engineer with strong BI skills to own the data foundation behind our financial products. You will build reliable pipelines that bring financial transactions and market data into a well-modeled SQL Server data warehouse, and turn that data into dashboards and insights that business teams trust. You will use AI-assisted tools to deliver faster without compromising quality. Key Responsibilities 1. Data Pipelines & Integration · Build and maintain batch and streaming pipelines for financial transactions and market data. · Develop ETL/ELT processes that ingest, validate, and transform data from databases, APIs, internal services, and third-party platforms. · Automate workflows, monitor pipeline health, and optimize performance as data volumes grow. 2. Data Warehouse & Modeling · Design and evolve the SQL Server data warehouse using dimensional modeling (fact and dimension tables, star schemas). · Optimize data storage across operational databases, the data warehouse, and data lake environments. · Define business metrics and KPI logic, and build reusable datasets and views as a single source of truth. 3. Business Intelligence & Dashboards · Build and maintain interactive dashboards and reports in Power BI, Metabase, or similar tools. · Translate business requirements into meaningful KPIs and visualizations for operations, finance, marketing, and product teams. · Analyze transaction data to uncover trends and patterns, and support ad hoc analysis with actionable insights. 4. Data Quality & Reliability · Implement validation and data quality checks across pipelines and dashboards. · Reconcile data between sources and reports; investigate and resolve discrepancies. · Perform root cause analysis on failures and bottlenecks, and drive improvements to code and architecture. · Document data sources, transformations, data models, and dashboards. 5. AI-Assisted Engineering · Use AI coding assistants and agents to accelerate SQL and Python development, pipeline implementation, debugging, and performance tuning. · Automate repetitive data engineering tasks and streamline analytical workflows with AI. · Review, test, and validate AI-generated code to ensure it is accurate, secure, and production-ready. · 4+ years of experience in data engineering, BI development, or analytics engineering. · Proficiency in Python, with a focus on clean, maintainable code. · Proven experience building ETL/ELT pipelines and integrating data from databases, APIs, and other sources. · Solid understanding of dimensional modeling (fact and dimension tables, star schemas). · Practical experience with BI tools such as Power BI, Metabase, Tableau, or Apache Superset. · Understanding of data quality, data validation, and pipeline monitoring. · Experience using AI-assisted development tools in daily work, with the judgment to critically review their output. · Strong analytical and problem-solving skills, attention to detail, and the ability to translate business needs into technical solutions. · Experience with financial, payments, or trading data.