Data Engineer Onsite Evening Shift Lahore PKR Salary

Job Description

• 6+ 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.