Data Engineer (Onsite, Evening Shift, Lahore, PKR Salary)

Requirements:

• 3+ years of experience in a data-focused role (Data Scientist, Data Analyst, Business Intelligence).
• Strong command of SQL with experience writing optimized queries (joins, aggregations, filters, CTEs).
• Proven experience in data cleaning, transformation, and ETL/ELT workflows.
• Experience using Databricks or similar platforms for data processing, notebooks, or workflow management.
• Experience building dashboards using tools like Metabase, Tableau, Looker, or Power BI.
• Ability to create clear and intuitive dashboards for non-technical stakeholders.
• Strong analytical thinking, with the ability to translate data into insights and insights into actionable recommendations.
• Excellent communication skills, with the ability to explain complex findings in a simple and clear manner.
• Highly organized, detail-oriented, and capable of managing multiple projects concurrently.
• Proactive and comfortable working in a dynamic, fast-paced environment.
• Experience with machine learning techniques (regression, classification, clustering, forecasting).
• Familiarity with Python or R for data analysis, modeling, or automation.
• Exposure to SaaS or healthcare datasets.
• Experience working with large datasets or cloud data warehouses (Snowflake, BigQuery, Redshift).
• Experience with data governance, metadata management, or setting up data catalogs

Responsibilities:

• Define, manage, and optimize the data pipeline, ingestion from internal systems, external sources, APIs, etc.
• Clean, validate, and transform raw data to prepare it for analysis and reporting.
• Conduct exploratory data analysis to identify trends, patterns, anomalies, and business opportunities.
• Write efficient SQL queries to extract data, build metrics, and support business decisions.
• Build dashboards, visualizations, and automated reports for cross-functional teams.
• Collaborate with product, engineering, operations, and leadership to understand data needs and provide actionable insights.
• Monitor data quality, integrity, and performance; proactively detect and resolve issues.
• Maintain documentation for datasets, definitions, dashboards, and key metrics.
• Promote a data-driven culture by enabling teams to use data confidently and effectively.
• Continuously evaluate and recommend improvements to the Companys data tools, architecture, and processes.

Work Schedule:
03:00 PM - 12 AM