Data Analytics Engineer

Candidates typically face a timed online aptitude test followed by a technical interview focusing on SQL queries, Python data‑manipulation tasks, and a mini‑case study on dashboard creation. The HR round assesses communication skills and cultural fit. Preparation should include practicing data‑analysis scenarios and reviewing basic statistics.

IT & Digital Solutions fosters a collaborative atmosphere with a strong emphasis on learning and mentorship. Employees enjoy a balanced work‑life schedule, regular hackathons, and clear pathways for skill advancement.

Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or related quantitative field; minimum 60% aggregate (or CGPA 6.0/10); batch 2025‑2027; no active backlogs at the time of joining; strong foundation in SQL and programming (Python/R).

Round 1: Online Aptitude Test (Logical Reasoning, Quantitative & Data Interpretation) → Round 2: Technical Interview (SQL, Python coding, case‑study on data analysis) → Round 3: HR Interview (fitment, career goals, cultural fit)

IT & Digital Solutions is a fast‑growing technology services firm that partners with enterprises across banking, retail, and healthcare to deliver end‑to‑end digital transformation. With a workforce of over 2,000 professionals, the company prides itself on a culture of continuous learning, innovation, and customer‑centric delivery. The firm has consistently been recognized for its agile project methodology and its emphasis on upskilling employees through internal academies and certifications. As a Data Analytics Engineer, you will be at the heart of the organization’s data ecosystem. Reporting to the Head of Data Engineering, you will collaborate with data engineers, scientists, and business analysts to design, build, and maintain robust data pipelines that feed analytical platforms. Your work will directly influence strategic decisions, helping business units turn raw data into actionable insights. **Key Responsibilities** 1. Conduct exploratory data analysis on large, heterogeneous datasets to uncover trends and patterns. 2. Develop and fine‑tune statistical models and machine‑learning algorithms for predictive analytics. 3. Design, build, and maintain interactive dashboards and reports using Tableau, Power BI, or similar tools. 4. Work closely with data engineers to integrate, transform, and validate data from multiple sources ensuring high data quality. 5. Perform data profiling, cleansing, and enrichment activities to maintain reliable data assets. 6. Gather requirements from business stakeholders, translate them into analytical tasks, and deliver clear, actionable insights. 7. Automate recurring reporting workflows, set up scheduling and alert mechanisms for timely delivery. 8. Communicate findings effectively to both technical and non‑technical audiences, influencing decision‑making. 9. Stay abreast of emerging analytics tools, best practices, and industry trends, and propose improvements to existing processes. 10. Mentor junior analysts and contribute to a knowledge‑sharing culture within the team. **Tech Stack**: SQL, Python (pandas, NumPy, scikit‑learn), R, Tableau/Power BI, Git, Linux, cloud platforms (AWS/GCP), Airflow or similar orchestration tools. **Growth Path**: Starting as a Data Analytics Engineer, high performers can progress to Senior Analyst, Lead Data Analyst, and eventually to Data Analytics Manager or Head of Analytics, with opportunities to specialize in data science or data engineering. **Why Join IT & Digital Solutions?** The company offers a vibrant work environment where fresh talent is trusted with real‑world projects from day one. Employees benefit from structured learning programs, competitive compensation, and clear career progression. If you are passionate about turning data into business value and thrive in a collaborative, fast‑paced setting, this role provides the perfect launchpad for a rewarding analytics career.