Job description
Job Details:
Duration :
6-Month
We are seeking a
Data Analytics Engineer
to design and maintain ETL pipelines, automate
data workflows, and create insightful visualizations.
The ideal candidate will have expertise
in
SQL (MS SQL, PostgreSQL, Oracle), Python, APIs, SSIS/SSRS
, and
data
visualization tools
like Power BI and Tableau.
This role involves
data mining,
transformation, and business intelligence
, ensuring data is accessible, optimized, and
effectively visualized for decision-making.
Key Responsibilities
• Design, develop, and maintain ETL pipelines using SQL, SSIS, and Python.
• Extract, transform, and load (ETL) data from APIs and multiple data sources into
relational databases.
• Query, optimize, and manage databases, including MS SQL Server, PostgreSQL, and
Oracle.
• Automate data workflows and pipelines using Python (pandas, NumPy, SQLAlchemy).
• Build and maintain SSRS reports and dashboards for reporting and insights.
• Develop interactive data visualizations using Power BI and Tableau to support
business intelligence.
• Ensure data integrity, consistency, and governance across systems.
• Collaborate with cross-functional teams to provide data-driven insights.
• Assist in database performance tuning and optimization strategies.
Required Technical Skills
Programming & Scripting:
• SQL: Strong proficiency in writing complex queries, stored procedures, functions,
and views.
• Python: Experience with pandas, NumPy, SQLAlchemy, and automation scripts.
• SSIS (SQL Server Integration Services): Experience in designing and maintaining ETL
processes.
• SSRS (SQL Server Reporting Services): Experience in building reports and dashboards.
• APIs: Ability to extract, transform, and load (ETL) data from RESTful APIs into
databases.
Database Management:
• Experience with MS SQL Server, PostgreSQL, and Oracle.
• Stored Procedures & Views: Proficiency in writing optimized stored procedures,
functions, and database views.
• Strong experience in database schema design, indexing strategies, and performance
tuning.
• Experience in data security, role-based access, and governance best practices.
• Power BI & Tableau: Strong experience in creating interactive dashboards and
reports.
• Ability to present complex data in a clear, visually compelling, and actionable
format.
• Experience with DAX (for Power BI) and creating calculated fields/measures.
Data Engineering & Automation:
• Expertise in data wrangling, transformation, and preprocessing.
• Python-based workflow automation and ETL pipeline development.
• Experience with batch and real-time data processing.
• Knowledge of data warehousing concepts and database optimization techniques.
Analytical & Statistical Skills
• Descriptive Statistics: Knowledge of probability, hypothesis testing, and distributions.
• Data Interpretation: Ability to extract actionable insights from datasets.
• Problem-Solving: Identifying trends, patterns, and anomalies to improve processes.
Soft Skills
• Communication: Ability to translate complex technical concepts to non-technical
stakeholders.
• Collaboration: Experience working across departments, engaging with analysts and IT
teams.
• Self-Starter: Ability to take initiative and work independently on data challenges.
Preferred Qualifications (Nice-to-Have):
• Experience with cloud-based data solutions (Azure SQL, AWS RDS, Google BigQuery).
• Familiarity with big data processing frameworks (Spark, Hadoop, Databricks).
• Knowledge of Docker and containerization for ETL workloads.
Required Skill Profession
Other General